This page contains a list of Master projects that are currently available in Life Sciences (SV) or in STI-IBI laboratories. These projects can be searched by keywords. If you are interested or would like to obtain further information from the Lab, please use the contact email listed.
Note that if you are interested in an interdisciplinary project (one where you will be co-supervised by two labs from different EPFL Schools), you can type ‘interdisciplinary’ in the search box.
| Laboratory | Title | Category |
| De Los Rios | Optogenetic control of TDP-43 oligomerization to investigate the yeast Protein Quality Control machinery The failure of cellular protein homeostasis, or proteostasis, is a fundamental issue underlying many late-onset neurodegenerative disorders, including Alzheimer’s, Parkinson’s, amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD), and many more collectively referred to as proteinopathies. These diseases are associated with the accumulation of toxic misfolded and aggregated proteins. Cellular protein quality control (PQC) involves both degradation mechanisms, such as the ER-associated degradation (ERAD) pathway, and repair mechanisms such as molecular chaperones, which utilizes ATP hydrolysis to unfold, refold, or disaggregate misfolded proteins. In yeast, the Hsp70 system works in conjunction with co-chaperones (Hsp40s such as Sis1 and Ydj1, Hsp110, and Hsp104) to remodel protein aggregates. However, it remains unclear how PQC components partition between competing substrates and what factors determine their binding affinities in a densely packed cellular environment. TDP-43, an RNA-binding protein associated with ALS and FTLD, forms aggregates in both human neurons and yeast models. By optogenetically controlling its oligomerization , we can investigate PQC dynamics in real time under specific cellular stress conditions. We hypothesize that optogenetically induced TDP-43 oligomerization will recruit PQC chaperones (Hsp70, Hsp40, Hsp104, Hsp110) differently, in the context of other protein misfolding stress, thus revealing the principles of chaperone partitioning and client affinities. The master’s student will first develop a Cry2-based optogenetic system to control TDP-43 oligomerization and assembly in yeast under conditions of proteostasis stress. Subsequently, he will quantify the partitioning of PQC chaperones (Hsp70, Hsp40s, Hsp110, and Hsp104) in response to controlled TDP-43 oligomerization through live-cell fluorescence microscopy of fluorescently tagged chaperones. Co-localization analysis will be conducted to assess recruitment dynamics, along with a proximity based proteomics approach. Additionally, affinity measurements will be performed using in-vitro fluorescence resonance energy transfer (FRET). This project aims to uncover how chaperones partition between clients in-vivo, providing mechanistic insights into the principles of PQC under proteotoxic stress. The findings could suggest strategies for re-engineering chaperone allocation in the context of protein misfolding diseases in the future. Keywords: Protein homeostasis, chaperones, optogenetics, yeast Supervisor: Paolo De Los Rios Co-supervisor: Satyam Tiwari Contact: [email protected], [email protected] Required: Basic cell biology Posted in December 2025 |
Cell biology Wet |
| De Los Rios | Label‑free single‑particle quantification of Hsp70–Hsp40–client assemblies using mass photometry ATP‑dependent chaperones, particularly the Hsp70 machinery, prevent proteotoxicity by binding misfolded and aggregated clients, such as TDP-43, by forming dynamic higher‑order assemblies that disassemble over time. However, current ensemble assays obscure details about stoichiometry, oligomeric states, and time‑resolved mass changes within this heterogeneous landscape. A label‑free, single‑particle, quantitative workflow would shed light on how chaperone–co‑chaperone (Hsp70-40) interactions and client binding influence the mechanism and efficiency of this protein repair process. In this master’s project, the student will aim to establish interferometric scattering (iSCAT) microscopy (aka mass photometry) as a calibrated, label‑free platform for quantifying masses and Hsp70–Hsp40–client assemblies. The hypothesis is that nucleotide‑state–dependent Hsp70 self‑association and specific Hsp70–Hsp40 hetero‑oligomers regulate client remodelling, which can be observed and quantified in real time with iSCAT. The initial steps include building and calibrating iSCAT for chaperone assemblies, generating contrast‑to‑mass calibration using protein standards, and performing orthogonal validation with native-PAGE, or negative‑stain TEM. Detection limits for monomers up to higher‑order oligomers will be established under nucleotide-free, ATP, and ADP conditions. Subsequently, the project will focus on quantifying the oligomeric states of Hsp70 and Hsp40 and their hetero‑complexes, mapping nucleotide-dependent self‑association of Hsp70, and oligomers of J‑domain proteins such as Hsp40. The work will include resolving Hsp70–Hsp40 stoichiometries and affinities, deriving equilibrium constants, and analysing mass distributions across physiological concentrations. Finally, the student will investigate client engagement and time‑dependent remodelling using biosensors like misfolding‑prone MLucV and MTDP43V. This involves quantifying the masses of chaperone–client complexes and monitoring aggregation and oligomerisation kinetics. The methodology involves label-free, single-particle mass quantification of chaperone assemblies with temporal resolution, complemented by orthogonal biophysical validation techniques such as TEM (for high-resolution imaging) and FRET (to report on client folding and activity in real-time). Preliminary data support the feasibility of these experiments, demonstrating the accurate detection of native MLucV (~120 kDa), apo Hsp70 (~70 kDa), and the observation of distinct higher-order oligomeric states indicative of self-association. Keywords: protein aggregation, haperones, mass photometry Supervisor: Paolo De Los Rios Co-supervisor: Satyam Tiwari Contact: [email protected], [email protected] Required: – Posted in December 2025 |
Molecular biology Wet |
| Gönczy | Contact guidance in blebbing cancer cells using nanostructured substrates The Cell Dynamics and Fragmentation Laboratory is a newly established research group at EPFL, founded as part of the Ambizione project “Molecular and Physical Basis of Cell Fragmentation” and hosted at the unit of Pierre Gönczy. Our research aims to uncover how cells break into distinct, biologically active fragments outside of classical cell division. This phenomenon occurs in cancer progression, immune cell behavior, and developmental processes, yet the underlying mechanical and molecular principles remain largely unexplored. Cell fragmentation represents a unique intersection between biophysics, cell biology, and engineering. By combining advanced live-cell imaging, microfluidic technologies, molecular perturbations, and quantitative modeling, we investigate how forces, membrane tension, cytoskeletal activity, and lipid composition determine when and how cells fragment. Understanding these principles will allow us not only to explain unexplored biological behaviors, but also to engineer new experimental systems for studying cell mechanics and communication. The aim of this project is to investigate how nanoscale topographical cues guide the migration of cancer cells that rely on bleb-driven motility. Preliminary unpublished results indicate that nanofabricated ridges and grooves can steer blebby cancer cells in opposite directions depending on their migration mode and cytoskeletal organization. The aim of this project is to complete this study for publication, by expanding the dataset, refining the substrates, and quantitatively analyzing how nanotopographies modulate bleb formation, polarity, and guidance. Keywords: contact guidance, blebs, nanostructures, cancer cell migration Supervisor: Pierre Gönczy Co-supervisor: Juan Manuel Garcia Arcos Contact: [email protected], [email protected] Required: – Posted in November 2025 |
Bioengineering Dry and wet |
| Gönczy | Advanced live-cell imaging of membrane and cytoskeletal dynamics The Cell Dynamics and Fragmentation Laboratory is a newly established research group at EPFL, founded as part of the Ambizione project “Molecular and Physical Basis of Cell Fragmentation” and hosted at the unit of Pierre Gönczy. Our research aims to uncover how cells break into distinct, biologically active fragments outside of classical cell division. This phenomenon occurs in cancer progression, immune cell behavior, and developmental processes, yet the underlying mechanical and molecular principles remain largely unexplored. Cell fragmentation represents a unique intersection between biophysics, cell biology, and engineering. By combining advanced live-cell imaging, microfluidic technologies, molecular perturbations, and quantitative modeling, we investigate how forces, membrane tension, cytoskeletal activity, and lipid composition determine when and how cells fragment. Understanding these principles will allow us not only to explain unexplored biological behaviors, but also to engineer new experimental systems for studying cell mechanics and communication. This project will use advanced microscopy techniques to measure membrane tension, cytoskeletal dynamics, and organelle behavior in living cells during fragmentation.This will be done mainly using fluorescence lifetime probes such as Flipper-TR. Students will be trained on fluorescence lifetime imaging (FLIM) and confocal microscopy and will extract quantitative measurements from microscopy image datasets. This internship is in collaboration with BIOP, the bioimaging platform. Keywords: FLIM, confocal, TIRF, live-cell imaging Supervisor: Pierre Gönczy Co-supervisor: Juan Manuel Garcia Arcos Contact: [email protected], [email protected] Required: – Posted in November 2025 |
Bioengineering Dry and wet |
| Gönczy | Dynamics of membrane tension and cell deformation under oscillatory osmotic stress The Cell Dynamics and Fragmentation Laboratory is a newly established research group at EPFL, founded as part of the Ambizione project “Molecular and Physical Basis of Cell Fragmentation” and hosted at the unit of Pierre Gönczy. Our research aims to uncover how cells break into distinct, biologically active fragments outside of classical cell division. This phenomenon occurs in cancer progression, immune cell behavior, and developmental processes, yet the underlying mechanical and molecular principles remain largely unexplored. Cell fragmentation represents a unique intersection between biophysics, cell biology, and engineering. By combining advanced live-cell imaging, microfluidic technologies, molecular perturbations, and quantitative modeling, we investigate how forces, membrane tension, cytoskeletal activity, and lipid composition determine when and how cells fragment. Understanding these principles will allow us not only to explain unexplored biological behaviors, but also to engineer new experimental systems for studying cell mechanics and communication. The aim of this project is to analyze an extensive dataset of cells exposed to oscillatory osmotic shocks with varying frequencies, amplitudes, and waveforms (square, triangular, gradient). Determine how plasma membrane tension (Flipper lifetime) and cellular strain evolve in time, and quantify phase relationships or delays between these signals. Keywords: quantitative biology, Python, membrane tension, Kuramoto models Supervisor: Pierre Gönczy Co-supervisor: Juan Manuel Garcia Arcos Contact: [email protected], [email protected] Required: – Posted in November 2025 |
Bioengineering Dry |
| Gönczy | Identifying cell types prone to fragmentation and building a primary-cell panel The Cell Dynamics and Fragmentation Laboratory is a newly established research group at EPFL, founded as part of the Ambizione project “Molecular and Physical Basis of Cell Fragmentation” and hosted at the unit of Pierre Gönczy. Our research aims to uncover how cells break into distinct, biologically active fragments outside of classical cell division. This phenomenon occurs in cancer progression, immune cell behavior, and developmental processes, yet the underlying mechanical and molecular principles remain largely unexplored. Cell fragmentation represents a unique intersection between biophysics, cell biology, and engineering. By combining advanced live-cell imaging, microfluidic technologies, molecular perturbations, and quantitative modeling, we investigate how forces, membrane tension, cytoskeletal activity, and lipid composition determine when and how cells fragment. Understanding these principles will allow us not only to explain unexplored biological behaviors, but also to engineer new experimental systems for studying cell mechanics and communication. The aim of this project is to establish and characterize a panel of primary cells and cell lines that are likely to fragment in vivo. Evaluate their behavior under mechanical confinement and shear stress in vitro and create a reference dataset of fragmentation propensity across cell types. Keywords: cell biology, primary cells, cancer, differentiation Supervisor: Pierre Gönczy Co-supervisor: Juan Manuel Garcia Arcos Contact: [email protected], [email protected] Required: – Posted in November 2025 |
Bioengineering Wet |
| Courtine | Commissioning of a robotic platform for lower limb experiments in rodents The profound transformation in the lives of people suffering from spinal cord injury is well known. Our laboratory has been working with animal models to better understand how electrical spinal cord stimulation and rehabilitation can help patients recover sensorimotor function, with the ultimate goal of improving treatment and enhancing the quality of life of patients. To assess, evaluate, and quantify improvements in motor function, robotic platforms are essential. In this project, you will work on a robotic platform for assessing lower limb rehabilitation in mice. The prototype consists of a treadmill with body weight support for rats and mice. This project will encompass various aspects of device development, including design using 3D software such as SolidWorks or Catia, manufacturing and assembly of robot components, programming robot controls, and implementing different measurement parameters. Keywords: neuroscience, bioengineering Supervisor: Victor Perez Puchalt Contact: [email protected] Required: ‘Programming skills in (Python and/or C++, Matlab), Electromechanical prototyping, 3D design (SolidWorks, Catia, and/or Creo PTC) Posted in November 2025 |
Bioengineering Dry and wet |
| Correia | Experimental Characterization of de novo designed light-switching proteins While computational protein design succeeded in the predictable design of static protein structures, the design of proteins responsive to environmental stimuli remains challenging. We developed a computational design approach to design light-controllable proteins. Light-responsive proteins have been engineered and successfully applied to molecular biology. However, many of these proteins are unstable, have low expression, and are not amenable to rational protein engineering or customization. De novo designed proteins with a bottom-up designed light-switching mechanism might offer a more controllable and predictable alternative to systems derived from natural sources. The project aims to develop and execute experimental methods to quickly screen de novo designed proteins and the detailed experimental characterisation of identified candidate designs. The methods employed include, but are not limited to protein expression, protein purification, split luciferase assays, mass spectrometry, and cellular assays. Keywords: molecular biology, protein design, protein purification, light-responsive proteins Supervisor: Bruno Correia Co-supervisor: Nicolas Goldbach Contact: [email protected], [email protected] Required: Strong background in biochemistry, hands-on experience in the lab is a plus Posted in October 2025 |
Bioengineering Wet |
| Merten | Microfluidic single cell screening of tumor-reactive T-cells We have previously established droplet microfluidic platforms for screening antibodies at the single cell level (El Debs B et al., PNAS 2012, Shembekar N et al., Cell Reports 2018, Panwar J et al., Nature Protocols 2023). In these systems, tiny aqueous droplets surrounded by oil serve as miniaturized test tubes. The technology enables the screening of hundred thousands of antibodies in a single experiment and has led to the establishment of a startup company in 2017 (Veraxa). The aim of this project is the establishment of similar screening platforms for T-cell therapies. The successful candidate will establish single cell droplet microfluidic assays using patient-derived model systems. Prior experience with cell culture, PCR and/or NGS is a strong plus. Keywords: T-cell therapy, single cell analysis, microfluidics Supervisor: Christoph Merten Co-supervisor: Roger Diaz Codina Contact: [email protected], [email protected] Required: Full time master thesis Posted in October 2025 |
Cancer biology Wet |
| Merten | Microfluidics-guided personalized cancer immunotherapy We have previously established a microfluidic platform for testing therapy options directly on tumor biopsies from patients (Eduati F et al., Nature Communications 2018, Utharala R et al., Nature Protocols 2022, Mathur L et al., Nature Communications 2022). However, these platforms are not yet suited for predicting outcomes of immune therapies. The aim of this project is to establish different kinds of assays for assessing the efficient killing of cancer cells by T-cells. The primary readout will be based on light-sheet imaging. The successful candidate will optimize staining of different cell types using fluorescent antibodies and establish functional fluorescence assays. Prior experience with cell culture, imaging and/or image analysis is a strong plus. Keywords: cancer immune therapy, microfluidics, imaging Supervisor: Christoph Merten Co-supervisor: Tianhao Li Contact: [email protected], [email protected] Required: Full time master thesis Posted in October 2025 |
Cancer biology Wet |
| Maynard | Generation of an In Vitro Spine-Muscle Axis The spine is the central hub of our peripheral nervous system, innervating our muscles and relaying impulses received from the brain. In the Maynard lab we have extensive experience growing organoids which we now want to channel toward building a connected spine to muscle axis. The prospective student will work towards optimising protocols for the growth of human muscle tissue/ neuromuscular junction organoids on a microfluidic chip together with spine organoids. Setting up this model on chip will allow us to investigate the plasticity and fragility of the connection between these two tissues. Keywords: organoids, neuroscience, microfluidics, neural regeneration Supervisor: Ashley Maynard Contact: [email protected] Required: Mammalian cell culture (in 2D is enough) experience is a big plus. Posted in September 2025 |
Neuroscience Wet |
| McKinney | High-resolution Image analysis of secretion and killing in Mycobacteria tuberculosis Are you interested in high-resolution, quantitative microscopy and image analysis? In this project we are developing an image analysis platform that includes detection, tracking, single-cell quantification of mycobacteria-super-resolution reporter and their killing of Macrophages. The project lies in the (further) development and application of an image analysis platform to answer questions about the biological validation of killing mechanisms between different TB mutants, blocking or activating cellular signaling pathways and mouse and human Macrophage phenotypes. Secondly, the project allows for the application of next generation image analysis tool applications using machine learning and microscopic quantification. Keywords: confocal microscopy, Mycobacteria Tuberculosis Supervisor: John McKinney Co-supervisor: Luca Schlotheuber Contact: [email protected] Required: Either knowledge on biological assay development for imaging and cell culture OR: image analysis, bioinformatics and object detection, classifications pipelines (Yolo, Trackmate, high-resolution data independent tracking). Depending on the background of the student, it will result in more data or experimental driven project Posted in September 2025 |
Computational biology Dry and wet |
| Fantner | An AI-Integrated Conversational Interface for Atomic Force Microscopy In this project, we developed a chatbot by fine-tuning ChatGPT on the API of an in-house Atomic Force Microscope (AFM) to enable natural language control of the instrument. Instead of relying on coding, users can interact with the AFM through conversational commands, making the system more intuitive and accessible. The current version translates user instructions into API calls for common tasks such as setting imaging parameters or initiating scans. Building on this foundation, the next step is to expand the chatbot’s capabilities by designing and testing different experimental scenarios, retraining the model to improve accuracy, and systematically evaluating its performance in realistic use cases. A key focus of the project will also be to identify and implement the most effective methods for analyzing chatbot performance, including both technical accuracy and user experience. Ultimately, this work aims to create an AI-powered assistant that not only simplifies AFM operation but also enhances usability and efficiency, lowering technical barriers for researchers and enabling more flexible experimental design. Keywords: software development, AI, AFM, smart microscopy, Python Supervisor: Georg Fantner Co-supervisor: Zahra Ayar Contact: [email protected], [email protected] Required: Software development skill (Python is required, Java is a plus), general knowledge of machine learning (dataset preparation, training, evaluation), analytical skills. Posted in September 2025 |
Computational biology Dry and wet |
| Radenovic | Fluorescence Techniques for Exploring Biological Nanopore Mechanisms Nanopore sensing is emerging as a valuable tool for the characterization & sequencing of DNA, RNA and more recently proteins. State of the art biological nanopores are already commercially available in devices like the minion (Oxford Nanopore Technologies), the fundamental physics around nanopores however are poorly understood. By studying the ionic flux and perform imaging experiments with those nanopores we aim at understanding the nonlinear behaviors of biological nanopores: rectification and gating. Two phenomena which, if understood properly, could lead to serious advancements in the field of biological nanopores. Keywords: biological nanopores, microscopy, data analysis Supervisor: Aleksandra Radenovic Co-supervisor: Matteo Dal Peraro Contact: [email protected], [email protected] Required: Basic lab work, commitment and excitement. Posted in September 2025 |
Molecular biology Dry and wet |
| Bitbol | Modeling the evolution of spatially structured microbial populations Our group is developing mathematical models for the evolution of spatially structured microbial populations. We perform analytical calculations and numerical simulations of stochastic models to understand the impact of the spatial structure of a population on the fixation of mutants. Possible projects along these lines include studying specific models of antibiotic resistance evolution in spatially structured populations, to assess the impact of spatial structure on resistance evolution. Keywords: mathematical modeling, stochastic simulations, evolution, population genetics Supervisor: Anne-Florence Bitbol Contact: [email protected] Required: Taste for mathematical modeling and/or numerical simulations. Previous experience with stochastic simulations or with other numerical approaches is a plus. Posted in September 2025 |
Computational biology Dry |
| Bitbol | Studying the evolution of specific proteins with machine learning models Our group is developing machine learning models for the study of protein sequences and of protein-protein interactions. In particular, we recently developed ProtMamba, a protein language model which is aware of homology between proteins but does not rely on multiple sequence alignments and RAG-ESM, a model which makes pretrained protein language models aware of homology. We also developed ProteomeLM, a language model that reasons on whole proteomes spanning the tree of life. These models open several applications for investigating the evolution of specific proteins and of their interactions. Several projects are available, with the goal of discovering new information on specific biological systems through machine learning models. Keywords: protein sequences, machine learning, protein language models, evolution Supervisor: Anne-Florence Bitbol Contact: [email protected] Required: Interest and taste for computational approaches. Interest in proteins and/or in evolution. Previous computational experience is a plus. Posted in September 2025 |
Computational biology Dry |
| Fellay | Predicting Genetic Interactions with Contrastive Learning This project will develop and evaluate machine learning approaches to predict genetic interactions, i.e., cases where the combined effect of mutations in two genes differs from what would be expected from their individual effects. The focus will be on applying contrastive learning to protein and gene representations, enabling the model to learn features that capture functional relationships and interaction patterns. Large-scale datasets of known genetic interactions will be used to train and benchmark models, and the learned embeddings will be tested for their ability to generalize to novel gene pairs and provide mechanistic insights into disease-relevant interactions. Keywords: – Supervisor: Jacques Fellay Co-supervisor: Ali Saadat Contact: [email protected], [email protected] Required: Strong background in machine learning, mathematics, and Python programming is required. Posted in September2025 |
Computational biology Dry |
| Fellay | Gene Intolerance to Expression Variation This project will explore how sensitive different genes are to changes in expression, a concept referred to as gene intolerance to expression variation. To address this, a Promoter Damage Index (PDI) will be developed by quantifying the impact of naturally occurring genetic variants in promoter regions using large-scale population datasets. By integrating information on regulatory annotations and evolutionary conservation, PDI will measure how much promoter variation is tolerated for each gene. The results will be benchmarked against existing intolerance metrics and gene prioritization tools, and combinations with these methods will be tested to assess whether predictive power for essential genes and disease associations can be improved. Keywords: – Supervisor: Jacques Fellay Co-supervisor: Ali Saadat Contact: [email protected], [email protected] Required: Strong background in machine learning, mathematics, and Python programming is required. Posted in September 2025 |
Computational biology Dry |
| Guiducci | Separation of primary cell adipocytes by Deterministic Lateral Displacement This master thesis project focuses on the development of a novel Deterministic Lateral Displacement (DLD) platform tailored for sorting primary adipocytes obtained from human tissue biopsies. While DLD systems have demonstrated great potential in sorting various blood cell types, their application to isolating primary cells from tissue digestion remains largely unexplored. The goal of this project is to build upon a DLD device previously developed in our laboratory and expand its utility toward the efficient isolation of bone marrow adipocytes. The thesis will involve redesigning and optimizing the existing DLD platform to accommodate the unique characteristics of primary adipocyte samples. Key objectives include adjusting the critical sorting size, modifying microfluidic geometries to manage heterogeneous cell populations, and implementing strategies to prevent chip clogging. A significant part of the project will also focus on optimizing the biological pre-processing of the tissue biopsy. This includes refining the digestion protocol to preserve fragile adipocytes, removing lipid contamination, and achieving a monophasic cell suspension suitable for microfluidic sorting. The student will work closely with both the Laboratory of Life Sciences Electronics (CLSE-EPFL) and the Laboratory of Regenerative Hematopoiesis (Naveiras group-UNIL) to iteratively test and improve both the biological and engineering aspects of the workflow. Keywords: microfluidics, sorting, differentiation, sample preparationy Supervisor: Carlotta Guiducci Co-supervisor: Micaela Siria Cristofori Contact: [email protected], [email protected] Required: Someone with a background in bioengineering, biology or chemistry, but physics or microtechnology are also welcome. Posted in August 2025 |
Bioengineering Dry and wet |
| Dal Peraro | Large-scale analysis of protein binding interfaces using deep learning methods We have developed in-house tools PeSTo (Protein Structure Transformer, Krapp L. F. et al. Nat. comm. 2023), capable of predicting protein binding interfaces for proteins, nucleotides, small molecules, ions, lipids, and, in later versions, carbohydrates (PeSTo-Carbs, Bibekar P. et al. JCTC 2024). We now plan to apply PeSTo to the entire Protein Universe Atlas (Durairaj, J. et al. Nature 2023) to predict binding interfaces systematically. Furthermore, we aim to develop methods to cluster these interfaces based on both geometric and chemical features, with the goal of gaining key insights into dark proteins and uncovering previously uncharacterized functional potential across the protein universe. Keywords: structural bioinformatics, machine learning, graph theory Supervisor: Matteo Dal Peraro Contact: [email protected] Required: Some background in programming required. Some background in structural biology, machine learning and graph theory is desirable but not necessary. Posted in August 2025 |
Computational biology Dry |
| Antanasijevic | CryoEM-based Characterization of Vaccine- or Virus-Induced Antibodies The project will focus on the use of cryo-electron microscopy to study how monoclonal and polyclonal antibodies engage different viral antigens following a vaccination or natural infection. The main pathogens of interest are HIV, enteroviruses and flaviviruses. The specific project details will be tailored according to students background and preferences. Keywords: cryoEM, flaviviruses, enteroviruses Supervisor: Aleksandar Antanasijevic Contact: [email protected] Required: Strong background in Biochemistry Posted in August 2025 |
Infectious diseases Dry and wet |
| Goemans | Understanding the impact of protein synthesis inhibitors on a gut bacterium Antibiotics affect the human gut microbiota but some seem to affect it more than others. In this project, we want to understand at the molecular level why this is the case using specific antibiotics (protein synthesis inhibitors) and a model gut microbe, Bacteroides uniformis. During this Master Thesis, the student will work together with a PhD student in the lab and will learn about various microbiology techniques. Keywords: Microbiota, antibiotics, dysbiosis, protein synthesis Supervisor: Camille Goemans Contact: [email protected] Required: – Posted in 2025 |
Infectious diseases Wet |
| Goemans | AI-based discovery of novel antimicrobials The objective of this project is to work together with a computational post-doc who developed an AI model to predict novel antibiotics targeting specific bacterial proteins. During the Master Thesis, the student will be in charge of the experimental part of the project which will involve bacterial screening, MIC testing and follow-up experiments depending on the interesting compounds identified. Keywords: Antibiotics, screen, bacteria, AI Supervisor: Camille Goemans Contact: [email protected] Required: – Posted in 2025 |
Infectious diseases Wet |
| Zenk | Master Thesis Opportunity in Neural Organoid Maturation Human neural organoids are an established model for studying early human brain development in both health and disease. However, achieving a more mature brain-like state remains a significant challenge. This master thesis project aims to develop strategies to enhance the maturation of human neural brain organoids. The student will gain hands-on experience withmolecular biology and cell culture techniques, contributing to an exciting area of research in developmental neuroscience. The project will take place at Campus Biotech in Geneva in a lab focused on epigenetic regulation in human brain development. The student will work closely with a postdoctoral researcher, receiving direct supervision and training. We are looking for a motivated master’s student with a background in molecular biology, neuroscience, or a related field. Keywords: Brain organoids, Cell Culture, in vitro models Supervisor: Fides Zenk Co-supervisor: Marlena Wisser Contact: [email protected] Required: molecular biology, neuroscience Posted in 2025 |
Neuroscience Wet |
| Zenk | Master Thesis Opportunity in Modelling Neurodevelopment Approximately 3% of children are born with a neurodevelopmental disorder This master thesis project aims to establish a human induced pluripotent stem cell (iPSC) line expressing Cas9 to study the impact of different genetic perturbations on human brain development. The project will be primarily wet lab-based, with a strong focus on molecular biology, cell culture, and CRISPR-based genome editing. The student will gain hands-on experience in techniques such as iPSC culture, Western blotting, and potentially sequencing. The project will be conducted at Campus Biotech in Geneva in a lab focused on epigenetic regulation in human brain development. The student will work closely with a postdoctoral researcher, receiving direct supervision and training. We are looking for a motivated master’s student with a background in molecular biology, genetics, or a related field. Keywords: ICRISPR-Cas9, screen, single-cell genomics Supervisor: Fides Zenk Co-supervisor: Marlena Wisser Contact: [email protected] Required: molecular biology, genetics Posted in 2025 |
Neuroscience Dry and wet |
| McKinney | Bladder organoid- type model to track urothelial regeneration post Uropathogenic E.coli (UPEC) infection The project will focus on studying how the urothelium regenerates after a UPEC infection. Mainly using microscopy and a transwell based tissue model (established in the lab), we will look at whether the correct epithelial cell types regenerate upon chemical injury in our model, how does an injured tissue compares to a naive tissue in facing UPEC infection and if certain epithelial cell types form safe havens for UPEC and promote recurrence of infection. Keywords: Infection biology, tissue regeneration, cell culture, organoid and organ-on-chip, microscopy Supervisor: John McKinney Co-supervisor: Gauri Paduthol Contact: [email protected] Required: Preferred but not necessary – experience in cell culture, microscopy, microbiology Posted in 2025 |
Infectious diseases Wet |
| Lemaitre | Psychology of science Considering the impact of science on society, developing a better understanding of the social and psychological factors shaping the scientific community is important. Such a project requires bringing experts together, who truly understand academia and have experience in different fields, such as life sciences and social sciences. In this framework, we aim to explore three sets of psychological and sociological factors that are not usually associated with science that could however influence career success in academia. In particular, we aim to better understand how romantic relationships, personality, and thinking styles shape the scientific community and influence career progression in science. For this, we will use validated tools and measures to assess personality and cognitive traits and launch large-scale surveys as well as semi-structured interviews to gather and analyze data. By bringing together experts in social and psychological research with scientists working in experimental life science laboratories, we hope to generate a rich data set that will have a significant impact on the growing field of metascience. Our project has the potential to provide critical insights into implicit factors that drive the emergence and success of leaders, and thus has significant implications for the scientific community and beyond. Keywords: Psychology, datascience, metascience Supervisor: Bruno Lemaitre Contact: [email protected] Required: Expertise in datascience and programming Posted in 2025 |
Cell biology Dry |
| Lemaitre | Drosophila immunity The Drosophila antimicrobial response at the time of the Cas9/CRISPR gene targeting revolution The application of Drosophila genetics has generated insights into insect immunity and uncovered general principles of animal host defense. These studies have shown that Drosophila has multiple defense “modules” that can be deployed in a coordinated response against distinct pathogens. Today, Drosophila can be considered as having one of the best-characterized host defense systems among the metazoan. Until recently, a detailed understanding of the fly immune response was hampered by the difficulty of generating loss-of-function mutations as well as the technological limits of the RNAi approach. The Cas9/CRISPR revolution offers new opportunities to revisit in a systematic manner Drosophila immunity. At the interface between large-scale genomic studies that lack resolution and individual gene analysis that lack breadth, our laboratory has undertaken a meso-scale ‘skilled’ analysis of immune modules, notably by addressing the individual and overlapping function of large immune gene family. The aim of the master project is to characterize the function of host defense modules (ex. antimicrobial peptides, phagocytosis,….) or specific genes in immunity using powerful genetic approaches and various model of infection. This master training will provide expertise in innate immunity, Drosophila genetics, molecular biology working at the organismal level. Methods: Drosophila genetics, molecular biology, genomic, histology, microbiology, bioinformatic. Keywords: Genetics, infection, signaling, immunology Supervisor: Bruno Lemaitre Contact: [email protected] Required: A background in life science Posted in 2025 |
Infectious diseases Wet |
| De Los Rios | Protein disaggregation by the bacterial Hsp70 system In eukaryotes, protein disaggregation by the Hsp70 system is helped by proteins of the Hsp110 class (which is itself a subclass of the Hsp70 superfamily), along physics principles that are more and more understood. No such system has been identified in bacteria, although bacteria are known to be extremely effective at finding clever solutions. In this project we want to explore if the bacterial HscC member of the Hsp70 family could play a similar role, and to quantify the role of GrpE, another partner of Hsp70, has in protein disaggregation. Keywords: Protein disaggregation, Hsp70, bacterial cells Supervisor: Paolo De Los Rios Co-supervisor: Mathieu Rebeaud Contact: [email protected] Required: Enzyme assays, gel electrophoresis, photospectrometry, protein expression and purification Posted in 2025 |
Molecular biology Wet |
| Pardon | Novel Design of Microfluidic Mixers for Lipid Nanoparticle (LNP) Synthesis Lipid nanoparticles (LNPs) are emerging as essential vehicles for drug delivery, particularly in the fields of gene therapy, mRNA vaccines, and targeted therapeutics. Microfluidic technology presents a promising solution, but existing mixer designs have limitations in achieving LNP for targeted tissue-specific delivery application. This project aims to develop an innovative microfluidic mixer design for the synthesis of ligand-guided targeted Lipid Nanoparticles (tLNPs). By optimizing fluids mixing and testing novel materials, we seek to enhance the quality and consistency of tLNPs, crucial for targeted drug delivery of mRNA to the T cells. The research will involve prototype fabrication, mixing parameters optimization and experimental validation using in vitro cell culture. The project is an established collaboration between BET platform EPFL and Brain Tumor and Immune Cell Engineering lab UNIGE at AGORA research center. Requirements: -High motivation and interest in the topic -Wet-lab experience, cell culture, FACS, transfection methods -Knowledge of size-based molecule separation methods (SEC, ultrafiltration, dialysis) -Knowledge of state-of-the-art human gene therapy is a plus -Background in material sciences and particle characterization methods is a plus -Practical experience in microfluidics for biological application is a plus Application: To apply, please include a short motivation letter and your CV. Keywords: Lipid nanoparticles, microfluidic, FACS, tLNPs Supervisor: Gaspard Pardon Co-supervisor: Dzhangar Dzhumashev, UNIGE Contact: [email protected] Required: BSc or MSc student Posted in 2025 |
Bioengineering Dry and wet |
| Radenovic | Simulation for nanoparticle gating on solid-state nanopore To replicate gating functions in artificial solid-state nanofluidics implies significant understanding and applications for biosensing, drug delivery, and ionic-based computation such as neuromorphic computing, etc. In our lab, we have realized rapid and reproducible gating behaviors with nanoparticles (~30 nm in diameter) on the SiNx-based nanopores (sub-10 nm). To fully understand the gating mechanism in our system, and offer guidance for further optimization of the experimental performance, therefore, we are offering a master/semester project related to the COMSOL simulation of nanoparticle gating. The task of student will be to adapt the nanopore simulation model for our nanoparticle gating system, and to perform first numerical simulation in a stationary and symmetrical regime to understand how the nanoparticle affects nanopore conductance, and then develop non-symmetrical (with nanoparticle off-axis) simulation model to understand the gating performance. Keywords: Nanopore, nanoparticle gating, simulation Supervisor: Aleksandra Radenovic Contact: [email protected] Required: Basic knowledge of thermodynamics, electrostatics and fluidics; numerical simulation with Finite Element Method, ideally in COMSOL platform. – Posted in 2025 |
Bioengineering Dry |
| Schoonjans | Developing an Advanced Live Biotherapeutic Product for Intestinal and metabolic Health This project aims to optimize a microbiome-based approach to enhance the production of secondary bile acids, known for their role in promoting intestinal stem cell-mediated regeneration and gut barrier integrity. Methods: -Culture anaerobic bacteria and establish a bile acid-modifying bacterial consortium. -Assist in colonizing the mice with the selected bacterial strains. -Evaluate the colonization efficiency using qPCR and bile acid profiling. -Evaluate the therapeutic effects of the bacterial consortium through immunofluorescence stainings and transcriptomic analysis. Expected Outcome: Development of an advanced Live Biotherapeutic Product that could be used as a therapy to treat chronic gut disorders and obesity. Keywords: Microbiome, bile acids, intestinal stem cells, gut barrier Supervisor: Kristina Schoonjans Co-supervisor: Antoine Jalil Contact: [email protected] Required: Basic knowledge/skills in biochemistry, molecular biology and bioinformatics Posted in 2025 |
Molecular biology Dry and wet |
| Schoonjans | Metabolic Regulation of Liver Cell Function and Stress Response Join our research team to investigate how specific metabolites influence hepatic energy metabolism, oxidative stress resilience, and mitochondrial function. This project will provide hands-on experience with cutting-edge techniques in cellular metabolism and functional genomics. Key Techniques & Approaches: Metabolomics (LC-MS/MS, GC-MS) – Profile intracellular and extracellular metabolites to track metabolic fluxes. Transcriptomics (RNA-seq, qPCR, RT-qPCR) – Analyze gene expression changes in metabolic and stress response pathways. Mitochondrial Functional Assays (Seahorse XF, Oroboros O2k) – Assess mitochondrial respiration, ATP production, and metabolic flexibility. Oxidative Stress and Redox Biology (ROS detection, GSH/GSSG assays, NADPH measurements) – Investigate how cells manage oxidative stress. Advanced Cell Culture (Primary hepatocytes, 3D hepatic spheroids) – Study metabolic adaptations in physiologically relevant liver models. What You’ll Gain: Hands-on training in state-of-the-art bioanalytical techniques used in metabolic research. Experience in multi-omics data integration to understand metabolic regulation. The opportunity to contribute to a high-impact research project on liver metabolism. Keywords: Liver metabolism, mitochondria, cell biology, omics Supervisor: Kristina Schoonjans Co-supervisor: Hadrien Demagny Contact: [email protected] Required: Basic knowledge/skills in biochemistry, molecular biology and programming Posted in 2025 |
Molecular biology Dry and wet |
| Gönczy | Evolutionary diversity and origin of centriolar proteins Objective: identify homologues of fundamental centriolar proteins across the domains of life and thus help trace the origin of the centriole organelle. Approaches: computational biology, structural prediction, cell biology Ideal for students in: Computer Sciences, Life Sciences Keywords: AlphaFold, Foldseek, phylogenomics, centriole Supervisor: Pierre Gönczy Contact: [email protected] Required: – Posted in 2025 |
Computational Biology Dry |
| Gönczy | Analyzing centriole fate during zebrafish muscle formation Objective: monitor centrosome and centriole fate during muscle formation in zebrafish embryos. Approaches: 4D live imaging using light-sheet microscopy, injection of RNA/DNA into zebrafish embryos, develop and apply tracking algorithms to monitor centrosomes and centrioles. Ideal for students in: Life Sciences, Bioengineering. Keywords: Myogenesis, zebrafish, centriole, live imaging Supervisor: Pierre Gönczy Contact: [email protected] Required: – Posted in 2025 |
Developmental biology Dry and wet |
| Gönczy | Analyzing novel centriolar proteins in Chlamydomonas reinhardtii Objective: identify localization and test function of novel centriolar proteins in the green alga Chlamydomonas reinhardtii. Approaches: CRISPR/Cas9-mediated GFP tagging, as well as disruption, of novel centriolar proteins in Chlamydomonas reinhardtii, expansion microscopy, super-resolution microscopy. Ideal for students in: Life Sciences, Bioengineering. Keywords: Cell biology, centriole, CRISPR/Cas9, microscopy Supervisor: Pierre Gönczy Contact: [email protected] Required: – Posted in 2025 |
Cell biology Wet |
| Gönczy | Engineering a modified centriole duplication cycle in human cells Objective: engineer and analyze centriole duplication cycle with altered organelle number control. Approaches: molecular and cell biology, expansion microscopy, super-resolution microscopy, live imaging. Ideal for students in: Life Sciences, Bioengineering. Keywords: Molecular biology, cell biology, centriole, microscopy Supervisor: Pierre Gönczy Contact: [email protected] Required: – Posted in 2025 |
Cell biology Wet |
| Altug | MS Thesis/Internship Opportunity: Development of nanophotonic biosensors for detecting environmental contaminants Nanophotonic technologies are revolutionizing the field of biosensing, enabling the development of highly sensitive, cost-effective, and field-ready biosensors. At EPFL’s BIOS Laboratory, a patented nanophotonic platform has been developed to detect biomolecules with exceptional precision and speed. This project focuses on adapting the technology for environmental applications, aiming to detect small molecule contaminants. The work will involve designing innovative bioassays, integrating them with microfluidic systems for efficient sample processing, and implementing multiplexed detection to allow simultaneous testing of multiple contaminants. The goal of the project is to extend the capabilities of this biosensing platform to water monitoring. The project will also provide a unique opportunity to have interactions and collaborations with an early stage start-up (NEOSENS) that aims to tech transfer this powerful technology for real-world applications. Keywords: Biosensing, nanophotonics, bioassay development, environmental contaminants, tech transfer Supervisor: Abtin Saateh Co-supervisor: Marco Fumagalli Contact: [email protected] Required: Python data analysis Posted in 2025 |
Bioengineering Dry and wet |
| Petersen | Analysis of brain-wide neuronal selectivity during learning Understanding how individual neurons encode information is fundamental to deciphering brain function. Single-neuron measures of selectivity provide a mean to characterise how neurons respond to particular stimuli or task-related events, providing insights on the neural mechanisms underlying behaviour. The goal of this project is to quantify and model single-neuron measures of selectivity at a unique brain-wide scale, and explore how learning may shape this selectivity. We are looking for an outstanding and highly motivated student to help us in the data analysis. The project will enable the student to manipulate large datasets of spiking activity and implement advanced analysis methods. This project requires advanced programming skills (Python), experience with GLMs, machine learning, statistics, data visualization and an interest for neuroscience and behavior. Keywords: Reward-based learning, mice, neuronal code Supervisor: Carl Petersen Co-supervisor: Axel Bisi Contact: [email protected] Required: Python data analysis Posted in 2025 |
Neuroscience Dry |
| Petersen | Analysis of brain-wide neuron-to-neuron interactions during learning The mouse brain is a complex network of millions of neurons, each receiving and projecting signals to hundreds of other neurons. Recent advances in recording technologies allowed us to measure thousands of single neurons simultaneously during an associate learning task. Our unique large-scale dataset is amenable to the analysis of the concerted activity of many neurons in various brain regions during behaviour. The goal of this project is to quantify single-neuron interactions at a brain-wide scale, and explore how learning may shape these interactions. We are looking for an outstanding and highly motivated student to help us in the data analysis. The project will enable the student to manipulate large datasets of spiking activity and implement advanced analysis methods. This project requires advanced programming skills (Python), experience with signal processing, statistics, data visualization and an interest for neuroscience and behavior. Keywords: Reward-based learning, mice, neuronal code Supervisor: Carl Petersen Co-supervisor: Axel Bisi Contact: [email protected] Required: Python data analysis Posted in 2025 |
Neuroscience Dry |
| Petersen | Analysis of animal behaviour during learning In laboratory settings, video filming is used to monitor movements during behavioural paradigms. Machine learning tools, such as DeepLabCut, an open-source software tool for pose estimation, have facilitated the analysis and quantification of behaviour. Recent work has emphasized the influence of movement on neural activity as well as the richness of movement patterns that animals exhibit. The goal of this project is to explore and quantify orofacial movements of head-fixed mice that perform an associative learning task. More precisely, we seek to model possible relationships between movements and mouse decisions as the mouse learn the association of a sensory stimulus with a reward on a trial-by-trial basis. We are looking for an outstanding and highly motivated student to help us in the data analysis. The project will enable the student to manipulate rich behavioural data and implement advanced analysis methods. This project requires advanced programming skills (Python), experience with machine learning, statistics, data visualization and an interest for neuroscience and behavior. Keywords: Reward-based learning, behavior, mice Supervisor: Carl Petersen Co-supervisor: Axel Bisi Contact: [email protected] Required: Python data analysis Posted in 2025 |
Neuroscience Dry |
| Correia | Molecular Docking with Reinforcement Learning Molecular docking is notoriously challenging due to the extensive conformational space and low amount and quality of the available experimental data. Current methods often rely on traditional genetic algorithms or hill climbing, which makes them computationally expensive and limited in flexibility. Effectively, no existing solution is able to address molecular docking in a generalizable way. Given the similarities between docking and manipulation tasks in robotics, as well as advancement of reinforcement learning in control problems, we plan to introduce a reinforcement learning agent to explore the continuous action space of molecular torsion angles and rigid body transformations. This approach requires no training data and allows us to use customizable scoring functions based on first principles or established force fields. With possibility to train an agent on the entire proteome (i.e. using millions of AlphaFold models), the aim of this work is to address the existing generalizability problem in molecular docking and develop a more efficient and robust alternative to the traditional docking algorithms. Keywords: Machine learning, reinforcement learning, molecular docking, drug discovery Supervisor: Bruno Correia Contact: [email protected] Required: Machine learning background, good knowledge of Python and PyTorch. As a plus: experience in Reinforcement Learning and/or Robotics. Posted in 2025 |
Computational Biology Dry |
| Antanasijevic | Structural analyses of antibody-antigen interactions in the context of viral infections Electron microscopy allows to visualize antibody-antigen interactions with atomic-level precision which enables detailed studies of the underlying molecular mechanisms governing the immune response in the context of infection or immunization. In our lab we use these tools to identify common immunogenic signatures shared by individuals and develop algorithms for prediction and modulation of antibody-mediated immunity. Pathogens of interest include HIV, yellow-fever virus, dengue, rabies, SARS-CoV-2, and enteroviruses, while the matching antibody samples are obtained from human and animal sources. Specific antibody-antigen system for the Master Thesis project will be selected based on student’s preferences and sample availability. The project typically includes the biochemistry component (“wet lab”), imaging on state-of-the-art electron microscopes and data processing using HPC resources on campus (“dry lab”). Keywords: Virus, antibody, immunity, cryoEM Supervisor: Aleksandar Antanasijevic Contact: [email protected] Required: Strong background in Biological Chemistry, Chemistry and Physics, Participation (or intention to participate) in the BIO-315 course on Structural Biology Posted in 2025 |
Infectious diseases Dry and wet |
| Protein Production and structure Core Facility | High-Throughput Cell-Free Expression for protein designs This master’s project aims to overcome the limitations of traditional protein production methods using living cells, such as E. coli, mammalian, or insect cells. With a growing number of in silico designed proteins requiring rapid testing for expression and folding in 96/384-well formats, the most efficient solution is in vitro cell-free expression, which is easily automatable. The project will focus on developing new cell-free expression systems, including mammalian cell extracts, to improve protein folding accuracy. Additionally, it will establish a streamlined workflow from cell-free expression to binding assays, accessible to the EPFL community. This work will be carried out in collaboration with four research labs from the SV-STI faculties and one EPFL spin-off start-up, contributing to more efficient and scalable research in protein engineering and fostering innovation within the EPFL ecosystem. Keywords: Protein design, biotechnology, cell-free expression, target validation Supervisor: Florence Power Co-supervisor: Kelvin Lau Contact: [email protected] Required: Wet lab experience in molecular biology Posted in 2025 |
Bioengineering Wet |
| Ramdya | Build a robotic fly Nature has solved numerous challenges associated with autonomous behavioral control. We hope to leverage these solutions in robotics. The goal of this project is to construct an insect-inspired robot and to test bioinspired algorithms of limb control. This project at the interface of robotics and biology will be supervised at the Neuroengineering Laboratory in collaboration with EPFL robotics groups. Please email your CV, Bachelor (and if relevant Master) grades. Keywords: Robotics, biomechanics, control Supervisor: Pavan Ramdya Contact: [email protected] Required: Microfabrication and/or Electronics experience Posted in 2025 |
Bioengineering Dry and wet |
| Ramdya | Use robotic systems to automate biological experimentation Biological experiments often require skill and extensive training. They can also be repetitive. The objective of this project is to democratize and automate experimentation by developing automated vision-guided robotic systems that perform behavioral and/or neural studies. This project at the interface between robotics and neurobiology will be supervised at the Neuroengineering Laboratory, possibly in collaboration with the Microrobotics Laboratory. Please email your CV, Bachelor (and if relevant Master) grades. Keywords: Robotics, neuroscience Supervisor: Pavan Ramdya Contact: [email protected] Required: Robotics / electronics, programming experience Posted in 2025 |
Bioengineering Dry and wet |
| Ramdya | Study the full graph (connectome) of the fly nervous system It has recently become possible to analyze the connectome (a graph representing the connections between every neuron in the brain or motor system of the fly. The goal of this project is to further improve and explore this graph to answer specific questions about neural circuit motifs underlying complex motor behaviors. This project at the interface of computer science, mathematics, and biology will be supervised at the Neuroengineering Laboratory. Please email your CV, Bachelor (and if relevant Master) grades. Keywords: Network analysis, neuroscience Supervisor: Pavan Ramdya Contact: [email protected] Required: Python Posted in 2025 |
Neuroscience Dry |
| Ramdya | Use computational tools to study animal behavior Insects generate complex behaviors even with a numerically small nervous system. But what exactly is a ‘behavior’? How can we quantify and segment individual actions from one another? The objective of this project is to leverage computational and machine learning approaches to study the behavior of flies. These behavioral sequences can then be linked to simultaneously acquired neuroimaging data. This project at the interface of computer science, and neuroscience will be supervised at the Neuroengineering Laboratory, possibly in close interaction with computer science laboratories on campus. Please email your CV, Bachelor (and if relevant Master) grades. Keywords: Machine learning, computer vision, animal behavior, neuroscience Supervisor: Pavan Ramdya Contact: [email protected] Required: C/C++, and/or Python Posted in 2025 |
Computational Biology Dry |
| Ramdya | Use computational tools to study neural circuit activity A central goal of neuroscience is to link neural activity and behavior. The objective of this project is to use computer vision and machine learning-based approaches to extract neural activity patterns during behavior and to make accurate predictions relating behavioral and internal states. This project at the interface between computer science and neurobiology will be supervised at the Neuroengineering Laboratory. Please email your CV, Bachelor (and if relevant Master) grades. Keywords: Computer vision, machine learning, neuroscience Supervisor: Pavan Ramdya Contact: [email protected] Required: Python and/or C/C++ Posted in 2025 |
Computational Biology Dry |
| Ramdya | Behavioral studies in the laboratory This project will provide hands-on experience working with flies in the laboratory. Specific goals of this project will depend on the needs of a particular research direction but will require an examination of how neural activation or other perturbations modulate animal behavior. The student will get the opportunity to design experiments and analyze their own data. This project in neuroscience will be supervised at the Neuroengineering Laboratory. Please email your CV, Bachelor (and if relevant Master) grades. Keywords: Neuroscience, behavioral science Supervisor: Pavan Ramdya Contact: [email protected] Required: Python Posted in 2025 |
Neuroscience Dry and wet |
| Radenovic | Fluorescence Techniques for Exploring Biological Nanopore Mechanisms Nanopore sensing is emerging as a valuable tool for the characterization & sequencing of DNA, RNA and more recently proteins. State of the art biological nanopores are already commercially available in devices like the minion (Oxford Nanopore Technologies), the fundamental physics around nanopores however are poorly understood. By studying the ionic flux and perform imaging experiments with those nanopores, we aim at understanding two mechanisms of biological nanopores: gating and oligomerization path. Two phenomena which, if understood properly, could lead to serious advancements in the field of biological nanopores. Keywords: Biological nanopores, fluorescent and electron microscopy, protein engineering Supervisor: Aleksandra Radenovic Co-supervisor: Matteo Dal Peraro Contact: [email protected] Required: Basic lab work, commitment and excitement Posted in 2025 |
Bioengineering Dry and wet |
| McCabe | Optimising a novel drug-inducible transgenic expression system The student will explore and refine a powerful new drug-inducible inhibitor of the UAS/GAL4 binary expression system, a cutting-edge tool in genetic studies. This system works like a remote control, allowing scientist to temporally control genetically encoded transgenics using a drug. This project will involve hands-on experiments such as: Parameter optimization: media types, drug concentration. Expression Validation: crossing flies with a drug inducible GAL80 repressor and fluorescent markers. Generation of a methodological pipeline: Analyzing data to improve system efficiency and responsiveness. Keywords: Genetics, tool development, optimization, neurogenetics Supervisor: Samuel Vernon Contact: [email protected] Required: – Posted in 2025 |
Neuroscience Wet |
| McCabe | Automated analysis of biological data sets The goal of this project is to design and develop a robust machine learning-based software solution to automate the analysis of biological data sets. The applicant will leverage advanced algorithms to process, analyse, and extract meaningful insights from morphological, functional and/or behavioral data sets with a goal to reduce the time and effort required for manual data processing. The masters project can cover several of the below areas of development subject to the students experience: Data Pre-processing: Develop and implement data cleaning, transformation, and normalization techniques to prepare raw data for analysis. Model Development: Create and optimize machine learning models for tasks such as classification, regression, anomaly detection, and clustering based on the specific data requirements. Testing & Validation: Implement rigorous testing, validation, and performance evaluation to ensure the reliability and accuracy of the system. Keywords: Neuroscience, machine learning, post-hoc analysis Supervisor: Samuel Vernon Contact: [email protected] Required: – Posted in 2025 |
Neuroscience Dry |
| McCabe | Drosophila NMJ Ageing Our lab has recently developed an adult Drosophila NMJ model to study behavioural, morphological and physiological hallmarks of ageing and degeneration in a high throughput model. This project will allow the candidate to utilize this preparation to study how modification of important synaptic proteins phenotypically manifest during age-linked synaptic degeneration. Due to the versatile nature of the preparation, the technical skills can adapt to the applicants specific interests and can encompass functional, morphological and/or behavioral techniques. Keywords: Neurodegeneration, ageing, neuromuscular junction Supervisor: Samuel Vernon Contact: [email protected] Required: – Posted in 2025 |
Neuroscience Wet |
| McCabe | Production of ALS-like artificial CSF Amyotrophic lateral sclerosis (ALS) is a deadly rare neurological disease of unknown etiology and for which no cure is available. In the lab, we use in vivo and in vitro models to try and understand molecular mechanisms underpinning the disease to develop therapeutic targets. This master’s project aims to conduct a meta-analysis of proteomic results on cerebrospinal fluid (CSF) from murine ALS models and human patients. The student will learn to perform systematic research and integrate and re-analyze datasets with bioinformatic tools. Results will help produce ALS-like artificial CSF, and isolate proteins affecting the neural substrate. Keywords: Neurodegeneration, proteomics, bioinformatics Supervisor: Samuel Vernon Contact: [email protected] Required: – Posted in 2025 |
Neuroscience Dry |
| McCabe | Predicting early hallmarks of Amyotrophic lateral sclerosis (ALS) Amyotrophic lateral sclerosis (ALS) is a deadly rare neurological disease of unknown etiology and for which no cure is available. In the lab, we use in vivo and in vitro models to try and understand molecular mechanisms underpinning the disease to develop therapeutic targets. This master’s project aims to determine synaptic alterations throughout the ALS progression and define early hallmarks predicting neurodegeneration. The study will be performed on groups of post- mortem murine spinal cords (naïve, carrying ALS mutations, and treated with gene therapy). The student will familiarize themselves with and master different histological techniques, microscopy, image reconstructions, and analyses. Keywords: Neurodegeneration, synapses, histology, microscopy Supervisor: Samuel Vernon Contact: [email protected] Required: – Posted in 2025 |
Neuroscience Dry and wet |
| Gallini | Genetically engineering keratinocytes to express fluorescently tagged oncogenes The generation of a construct for skin keratinocytes to simultaneously express multiple oncogenes or tumor suppressors tagged with distinct fluorophores, facilitating high-resolution in vitro and in vivo studies of cellular dynamics. Keywords: Cloning, lentiviral infection, imaging Supervisor: Sara Gallini Contact: [email protected] Required: Molecular Biology Posted in 2025 |
Cancer biology Wet |
| Center for Imaging | Various Master projects All Master projects available in the Center for Imaging are available (and updated) on this website. Please make sure you have a look! Supervisor: Check details on the website linked above Contact: Check details on the website linked above Posted in 2025 |
Bioengineering Dry and wet |
| Biomedical Imaging Group | Various Master projects All Master projects available in the Biomedical Imaging Group (BIG) are available (and updated) on this website. Please make sure you have a look! Supervisor: Check details on the website linked above Contact: [email protected] Posted in 2025 |
Cell Biology Dry and wet |
| Bunne | Various Master projects All Master projects available in the Bunne Laboratory are available (and updated) on this website. Please make sure you have a look! Supervisor: Charlotte Bunne Contact: [email protected] Posted in 2025 |
Computational Biology Dry |
| Pioletti | Investigation of the effects of degradation induced by different solutions on osteochondral tissue samples in vitro Osteoarthritis affects approximately 500 million people worldwide, with more than 50% being over the age of 65. With the aging population, this number is expected to increase in the coming years. This disease can significantly reduce the quality of life by making movements painful and difficult. Affected individuals may experience difficulties in participating in daily, professional, or social activities, leading to psychological distress. Although there is currently no definitive cure for osteoarthritis, several treatments can help alleviate the symptoms. To test these different treatments and analyze the regeneration processes, it is necessary to have an in vitro osteoarthritic model, which involves controlled cartilage degradation. In this context, we aim to test certain degradation solutions at different concentrations in vitro to develop a relevant model. This is why this master’s project was initiated. Part 1: Development of the support for osteochondral samples The student will need to design and print a support to hold the osteochondral samples. This support must be functional and suitable for use in a cell culture environment. Part 2: Testing different degradation solutions The student will prepare the samples and test different degradation solutions on them, placed on the support developed in Part 1. Part 3: Analysis of degradation tests The student will perform biochemical and histological/ immunological analysis on the samples obtained from the degradation tests conducted in Part 2. (Additional tests may be carried out if necessary.) Keywords: Design, 3D printing, explant culture, histology Supervisor: Dominique Pioletti Contact: [email protected] Required: Some experience in culture and CAD tools Posted in 2025 |
Bioengineering Dry and wet |
| Mathis | Deep learning-based neuro-musculoskeletal models for adaptive learning and control This project aims to develop a comprehensive biomechanical model of the adult mouse, integrating neural and musculoskeletal dynamics for studying motor control and learning. The project will aim to bridge our newly developed forelimb model with whole-body models in a physics-based simulation environment, to create an in silico framework that will bridge neural activity with body dynamics. This output platform will enable the comparison of neural recordings from sensorimotor areas to computational predictions, offering new insights into how internal models of the body are represented and updated in the brain. Keywords: Neuroscience, data science, deep learning, biomechanics Supervisor: Mackenzie Mathis Contact: [email protected] Required: Programming in Python Posted in 2024 |
Bioengineering Dry |