EDBB Open Positions

This page will be updated more often as we enter the Spring of 2020 and as the EDBB program will be informed of new positions becoming available for the June 17-19, 2020 Hiring Days event at EPFL. Meanwhile, do not hesitate to contact the laboratories which interest you to find out whether they have upcoming openings for PhD students.

Our multidisciplinary lab, Bionanophotonic Systems Laboratory (BIOS) is at the cross-section of nanotechnology, nanophotonics, biology and biochemistry. We are introducing next generation biosensor, spectroscopy and bioimaging technologies with direct impact on fundamental life sciences, early disease diagnostics, safety and point-of‐care testing. BIOS has world leading expertise in experimental nanophotonics (plasmonics, metamaterials), microfluidics, nanofabrication and system integration. We are addressing the key challenges of current bioanalytical tools by developing novel nanodevices that can enable label-free, ultra-sensitive, multiplexed, rapid and real-time measurements on biomolecules, pathogens and living systems. We are looking for a motivated PhD student to join BIOS for developing cutting-edge biosensing devices towards continuous monitoring of disease biomarkers. Please check our most recent publications to get an idea about the ongoing projects:

  • Rapid and Digital Detection of Inflammatory Biomarkers Enabled by a Novel Portable Nanoplasmonic Imager. Small, https://doi.org/10.1002/smll.201906108 (2019).
  • Ultrasensitive Hyperspectral Imaging and Biodetection Enabled by Dielectric Metasurfaces. Nature Photonics 13 p. 390-396 (2019).
  • Imaging-Based Molecular Barcoding with Pixelated Dielectric Metasurfaces. Science 360, p. 1105-1109 (2018).
  • Resolving Molecule-Specific Information in Dynamic Lipid Membrane Processes with Multi-Resonant Infrared Metasurfaces. Nature Communications 9, p. 2160 (2018).
  • Label‐Free Optofluidic Nanobiosensor Enables Real-Time Analysis of Single-Cell Cytokine Secretion. Small 14, 1870119 (2018).

Engineering powerful proteins with novel functions for cell engineering, synthetic biology and therapeutic applications
Protein design has made tremendous progress in recent years and is becoming central to synthetic biology applications including cell engineering approaches. For example, engineered proteins with customized signaling responses to disease-associated molecules provide promising and powerful new therapeutic agents for cancer immunotherapy, regenerative medicine and autoimmune disorders.
Our lab is developing and applying computational-experimental protein design approaches for engineering proteins with a wide range of novel functions. The technologies have been validated on simple proof of concepts (e.g. Feng et al., Nat Chem Biol 2017; Arber et al., Curr Opin Biotech 2017; Keri et al., Curr Opin Struct Biol 2018; Young et al., PNAS 2018; Chen et al., Nat Chem Biol in press). Using these approaches, we now aim at designing innovative and powerful protein nanomachines towards engineering synthetic living cells or for improving the anti-tumor responses of engineered immune cells in cancer immunotherapies.
Specific projects typically involve some aspects of computational protein modeling and design using the techniques developed in the lab complemented by the directed evolution of desired protein functions and validation of engineered cells using a variety of
cell biology approaches. Collaboration with laboratories at the CHUV/UniL/Ludwig Institute for Cancer Research (e.g. Caroline Arber, George Coukos) are in place for testing engineered molecules and cells in mouse xenograft models before potential
translation to the clinic. Marrying empirical and computational protein engineering approaches has the unique potential to design a broad spectrum of cellular functions for engineering powerful cells with novel synthetic or sustained anti-tumor responses.

Exploring patterns of surface proteins on the cell membrane using selective-binding with DNA precision particles. 

We will exploit multivalency of rigid nanoparticles to achieve selective cell binding and characterise (dynamic) protein patterns on the cell surface. 

Insights can be used for diagnostics as well as understand and manipulate cell-adhesion and surface signalling pathways.

PhD project no. 1:

Characterization of spatiotemporal organization of the brain lipidome

Neural cells produce thousands of different lipids, each endowed with peculiar

structural features and contributing to specific biological functions. Lipid composition

affects neuron firing properties influencing vesicle fusion and fission processes,

membrane conductivity, and ion fluxes. Nonetheless, a systematic and fine-grained

characterization of lipid composition in the different brain regions is not available.

Lipids also play a fundamental role in brain development. For example, some lipids,

such as glycosphingolipids, mediate cell-cell recognition, others like steroid hormones,

and phosphoinositides, have a role in stimulating cell growth and signaling.

Furthermore, exposure to teratogenic agents, during development, is associated to

cognitive or sensory impairments that might be mediated by interference of these

teratogens with lipid biogenesis and metabolism. However, little is known about how

the regional specificity of lipids is developmentally established and maintained

throughout adulthood.

The doctoral candidate will aim at filling this gap by collecting systematic data

necessary to construct a high spatially resolved atlas of the lipidome of the adult and

developing mouse brain. We expect this resource to provide numerous cues of the

underlying regulation mechanisms; the most interesting observations will be

experimentally followed up by the candidate and related to function.

The project offered jointly by the La Manno and D’Angelo labs will allow the candidate


– Use super-resolved Imaging Mass Spectrometry (IMS) to reconstruct the spatial

lipidome in serial brain sections from adult and developing mice.

– Assess the lipid deregulation resulting from the exposure of different teratogenic


– Investigate the relation between the lipidome of different stem cell populations and

their neural progeny.

– Investigate how perturbation to genes involved in lipid metabolism affects brain development.

– Assess how direct perturbations of lipid composition affect morphogenesis and adult brain structure and composition.

PhD project no 2:

Construction and analysis of a Lipid Brain Atlas

Single-cell and spatial transcriptomics technologies have matured significantly in the

last few years and are now extensively used to build comprehensive atlases of tissue

gene expression heterogeneity. However, while datasets of this kind are accumulating,

similar resources that describe biochemical heterogeneity of tissues are still lacking.

With the advent of super-resolved Imaging Mass Spectrometry, it is now possible to

efficiently and rapidly measure the biochemical composition of tissues at micronresolution.

Using the technique, the laboratories of Giovanni D’Angelo and Gioele La

Manno have recently found a substantial spatial organization of lipids in the brain, the

regional specificity found was significantly more extensive than previously believed.

In the brain, the role of lipids is crucial for different functions; for example, it

contributes to setting neuron firing properties, controls membrane conductivity and ion

fluxes. Analyzing this unexplored heterogeneity is likely to reveal new biochemical

processes and principles that characterize different neurons and brain areas. Our labs

are actively working to collect an extensive dataset to build a resource that will serve

as a powerful tool for neurochemical research.

The doctoral candidate will have a central role in this effort. She/he will develop new

computational methods to process, analyze, and organize this extensive dataset. We

expect the candidate to:

– Develop ad-hoc machine learning algorithms (e.g., latent variable decomposition,

deconvolution approaches) for the analysis and interpretation of spatial lipidomic data.

– Use the tools developed to analyze the regional heterogeneity of the mouse brain


– Organize this knowledge into a resource for the community.

– Construct a volumetric 3d model of the brain and register all the data obtained in this

reference frame.

– Integrate the lipid atlas with gene expression brain atlases and build principled models that can predict one data type from the other.


At least 2 openings are available for the April 15th, 2020 deadline. PhD projects will be available in the following two areas of research:

  1. Biological nanopores for single-molecule sensing

Nanopore sensing is a powerful single-molecule approach currently developed for the precise detection of biomolecules, as for instance in DNA and protein sequencing. Our laboratory is developing this technology exploiting the properties of biological pores. Recently, we showed that aerolysin, a pore-forming toxin, exhibits high sensitivity for single-molecule detection and can be ad hoc engineered for different sensing tasks. The goal of this project is to develop and characterize aerolysin-based nanopores as sensing devices to be applied for genome sequencing, proteomic analysis and disease diagnosis. The project is highly interdisciplinary, includes experimental and computational aspects and interactions with a diverse network of collaborators.  Students with a background in biochemistry, physics, bioengineering and computational sciences are encouraged to apply.

  1. Integrative modeling at the membrane-protein interface

Molecular interfaces are essential for the formation and regulation of all assemblies that sustain life, to define cellular boundaries and intracellular organization, and to mediate communication with the outer environment. Our laboratory has been studying the molecular mechanisms governing the association of proteins to their membrane interfaces in order to understand the functional implications of this interplay. Multiple projects are available that focus on the theoretical and computational investigation of the structural and dynamic properties of membrane protein systems. All of them are addressed in synergy with experimental collaborators to allow for an efficient integration of biochemical and biophysical data. Students with a background in biochemistry, physics, bioengineering and computational sciences are encouraged to apply.

Live cell transcriptomics 2.0

Since first developed in 2009, single cell transcriptomics (scRNA-seq) technologies have rapidly been adopted as essential tools to detangle complex cellular systems during development or disease at unprecedented resolution. However, scRNA-seq requires cells to be lysed during sample processing, preventing us from performing downstream functional assays. In response, we have been developing Live-seq, a live-cell transcriptome profiling approach that relies on fluidic force microscopy (FluidFM, Guillaume-Gentil et al., Cell, 2014) to extract a cytoplasmic sample, coupled to an in-house developed, highly sensitive low-input RNA-seq strategy (Chen et al., submitted). While Live-seq already allows us to profile single cell transcriptomes without cell lysis, the approach still suffers from limited throughput and efficiency. In collaboration with the Fantner lab, we are therefore envisioning a PhD project to transform the current Live-seq 1.0 approach in one that is easily implementable, fast and robust. This interdisciplinary project will involve aspects from mechanical engineering, electrical engineering, nanotechnology, cell biology and transcriptomics, so it is ideally suited for a student interested in the full spectrum of bioengineering. We anticipate that such a technological breakthrough will catalyze a large number of applications across systems, including how cellular heterogeneity is molecularly established, to which extent cell fate or cell response decisions follow deterministic versus stochastic principles, whether cell trajectories are reversible, or what the mechanistic root is of symmetric versus asymmetric cell divisions.

Scanning ion conductance microscopy

Scanning ion conductance microscopy (SICM) is an emerging scanning probe technique that uses a nano-capilary to sense ionic currents at nanometer resolution. The technique can be used for high resolution, 3D topographic imaging of living cells, as well as localized sensing of physiologically relevant parameters such as surface charge, mechanical properties, and ion-currents. Recently we have developed the world’s fastest SICM microscope to study membrane trafficking, cell differentiation and cell infection. In addition, we have developed a new measurement technique called scanning ion conductance spectroscopy. This technique uses SICM for nanopore sensing of single molecule translocations with high precision and throughput. This technique can be used for studying DNA-protein interactions, single molecule charge studies, and single molecule sequencing. We are looking for one to two students to explore the capabilities of the new high-speed SICM tool for nanoscale biology.

What you will learn:

  • nanoscale measurement and instrumentation science
  • single molecule/single cell biophysics
  • multimodal imaging (SICM/super resolution fluorescence)

What we are looking for in PhD students:

  • Good balance between engineering and biology knowledge
  • Good experimental skills
  • As this is a new technology and research area, we are looking for independent and creative students who are willing to explore novel but uncertain tracks.

One or two EDBB PhD positions are offered with a choice among the following three projects:

  1. Dissecting de novo centriole assembly mechanisms.


Centrioles are small organelles that are critical for forming cilia, and which exhibit a striking 9-fold radial symmetric arrangement of microtubules. In proliferating cells, centrioles assemble once per cell cycle next to an existing centriole, although centrioles can assemble de novo in some circumstances. We discovered components that are essential for the onset of centriole assembly across evolution. We deploy a multidisciplinary approach to uncover the principles by which these components govern organelle biogenesis.


Determine the sequential recruitment and the requirement of centriolar proteins during de novo assembly in cultured human cells. Investigate whether de novo assembly involves a phase separation mechanism and repurpose a high-speed atomic force microscopy (HS-AFM) assay to probe de novo organelle biogenesis. Moreover, investigate de novo centriole formation in the physiological setting of the water fern or of Naegleria.


Molecular biology, including CRISPR/Cas9 genome engineering, cell biology, live cell imaging, super-resolution microscopy (STORM, iSIM, Ux-EM-STED), cryo-electron microscopy, high-speed atomic force microscopy (HS-AFM), proteomics.

  1. Engineering SAS-6 proteins to decipher centriole assembly mechanisms


Centrioles are small organelles that are critical for forming cilia, and which exhibit a striking 9-fold radial symmetric arrangement of microtubules. In proliferating cells, centrioles assemble once per cell cycle next to an existing centriole and near orthogonal to it. We discovered that the evolutionarily conserved SAS-6 proteins self-assemble into 9-fold radially symmetric structures thought to template the formation of the entire organelle.


Engineer SAS-6 proteins to probe the mechanisms governing centriole assembly. This includes protein modification to alter the symmetry and the diameter of the centriole in human cultured cells. Moreover, chimera will be generated between SASA-6 proteins from different species to probe the underlying self-assembly mechanisms. Furthermore, SAS-6 proteins will be repositioned in human cultured cells to assay whether their geometry is key for imparting orthogonal assembly.


Protein modeling, molecular biology, including CRISPR/Cas9 genome engineering, cell biology, live cell imaging, super-resolution microscopy (STORM, iSIM, Ux-EM-STED), electron microscopy.


  1. Dissecting Cep135/Bld10p function in centriole assembly


Centrioles are small organelles that are critical for forming cilia, and which exhibit a striking 9-fold radial symmetric arrangement of microtubules. In proliferating cells, centrioles assemble once per cell cycle next to an existing centriole, although centrioles can assemble de novo in some circumstances. We discovered components that are essential for the onset of centriole assembly across evolution. We deploy a multidisciplinary approach to uncover the principles by which these components govern organelle biogenesis.


Discover mechanisms through which proteins located at the centriole periphery contribute to organelle biogenesis, both in proliferating cells and in a de novo setting. An initial emphasis will be on dissecting the function of Cep135/Bld10p.


Molecular biology, including CRISPR/Cas9 genome engineering, cell biology, live cell imaging, super-resolution microscopy (STORM, iSIM, Ux-EM-STED), structural biology, cryo-electron microscopy, high-speed atomic force microscopy (HS-AFM).

PhD position in hyperpolarized MRI molecular imaging
Hyperpolarized carbon-13 MRI is a novel molecular imaging technique capable to enhance MRI sensitivity thus enabling to monitor in real-time function, perfusion and metabolism using injected substrates. This Ph.D. thesis will focus on molecular imaging of hyperpolarized glucose for monitoring brain metabolism in real-time. The project involves developing and optimizing hyperpolarized MRI tools and implementing them in vivo in healthy rodents and disease models.
The laboratory of function and metabolic imaging (LIFMET), is equipped with two unique custom-designed hyperpolarization instruments (7 tesla and 5 tesla polarizers operating at 1K). These systems enable to push the sensitivity limits of HP MRI beyond what is feasible with commercial instrumentation. The project benefits from the CIBM platform including highly qualified technical staff composed of engineers and trained veterinarians.
The application including a motivation letter, the CV and two reference letters should be sent by email to:

[email protected]  and [email protected]

PhD candidates will be enrolled in an EPFL PhD program such as EDBB, EDPY, or EDEE.
For more information, you can contact Prof. Rolf Gruetter and/or Dr. Mor Mishkovsky

Understanding the cellular processes is crucial for making progress in medicine, biology, and biotechnology. These fields aim to characterize the behavior of the cell under different conditions to provide tools for personalized and precision medicine, green energy or efficient chemical production. Experimental approaches are currently generating an abundant amount of biological data and require computational methods to perform integrative analysis of the cellular processes.
In the Laboratory of Computational Systems Biotechnology, LCSB, we focus on cellular process modeling, large-scale computations, and data analysis, with the aim to develop mathematical models and novel methods of mathematical and computational analysis for e.g. systems biology, metabolic engineering, and prediction of novel biotransformations.
We have openings for two to three PhD positions with an expected starting time-frame of Fall 2020. The following research topics are offered:

  1. Machine learning techniques for designing large-scale and genome-scale kinetic models 
    This project aims to employ Generative Adversarial Neural networks (GANs), an emerging technique in the area of deep learning, to construct populations of large-scale and genome-scale kinetic models of metabolic processes in cellular organisms. The emphasis of model design will be on obtaining models that are consistent with the experimental observation and consistent with imposed criteria such as biological feasibility, cell bioenergetics, and other physicochemical constraints.
  2. Development of dynamic and hybrid models of cellular metabolism 
    The aim of this project is to develop kinetic models of of a model eukaryotic organism, S. cerevisiae, that will allow us to predict the metabolic responses to changes in cellular and process parameters. In the next phase, the candidate will improve further the predictive capabilities of models by integrating the protein expression system and regulatory interactions of this organism. This project is part of an EU project and will involve interdisciplinary collaboration with the experts in systems biology, synthetic biology, and metabolic engineering.
  3. Microbiome data analysis and modeling  
    In this project, we aim to develop mathematical models that describe the metabolic networks of individual organisms in microbial communities and the interactions through metabolites and competition for resources. We will also develop individual agent-based representations of bacterial motility and growth using adaptive metabolic networks for each agent-cell and study how metabolic interactions can give rise to spatio-temporal arrangements in microbial communities.

The inquiries about the positions and applications including a motivation letter and the CV letters should be sent by email to: [email protected] and [email protected].

Neurodegenerative Disease under the Microscope: A Multimodal Imaging Approach to Decipher Aggregation Networks using Huntington Inclusion Formation as a Model System

This joint interdisciplinary PhD project exploits synergies between the Lashuel laboratory (SV-BMI-LMNN) and the Radenovic laboratory (STI-IBI-LBEN). Research in LMNN focuses on applying chemistry and biology approaches to elucidate the mechanisms of protein misfolding and aggregation and their contribution to neurodegenerative diseases. LBEN works in the research field that can be termed single molecule biophysics. They develop techniques and methodologies based on optical imaging, biosensing and single molecule manipulation with the aim to monitor the behavior of individual biological molecules and complexes in vitro and in live cells.

Neurodegenerative diseases such as Alzheimer’s or Huntington’s disease (HD) pose one of the grand challenges for our society. They severely impact the quality of life; there is no cure and therapies only alleviate the symptoms. Recent evidence suggests that phase separation and subsequent phase transitions play a key role in protein aggregation of intrinsically disordered proteins such as Huntingtin. However, very little is known about molecular and cellular determinants of these transitions. We believe that the combination of unique expertise, biochemical tools to manipulate Htt structure and PTMs, and novel imaging modalities position us well to make progress that has great potential to address this knowledge gap and develop novel approach with wide-ranging applications in basic and translational neurodegenerative research. Towards this goal, we will apply single-molecule fluorescence super-resolution (localization microscopy, single particle tracking), phase microscopy and image analysis (deep learning) to directly study Huntington’s disease in cellular and neuronal HD model systems that are well characterized at the biochemical, biophysical, omics and ultrastructural levels. The project connects the expertise of the Radenovic lab in imaging technologies with the extensive know-how of neurodegenerative disease of the Lashuel Lab.

We seek highly talented, enthusiastic and exceptionally motivated candidates with a M.Sc. degree in (bio)physics with an affinity for (neuro)biology and biophysical chemistry. We also encourage candidates with a background in (neuro)biology with an interest in advanced microscopy to apply for this position.
Good communication skills and team spirit are important. Fluency in English is an absolute requirement; the candidate must be conversant and articulate in English speaking and should have strong writing skills. An interview and a scientific presentation will be part of the selection process.

The qualified candidate will benefit from working in a collaboration of two very dynamic and multidisciplinary groups in a highly collaborative and stimulating environment and will have access to state of the art laboratories and core-facilities and a competitive salary. For more information about the labs, please visit our websites and review our recent publications at:

The Lashuel laboratory: https://www.epfl.ch/labs/lashuel-lab/

The Radenovic laboratory: https://www.epfl.ch/labs/lben/

We’re always looking for talented PhD students. with following background : optics, electronics, optical and magnetic trapping, cell and molecular biology, polymer physics, nanotechnology, and clean room experience.

Engineering organoid morphogenesis

Organoids form through poorly understood morphogenetic processes in which initially homogeneous ensembles of stem cells spontaneously self-organize in suspension or within permissive three-dimensional extracellular matrices. Yet, the absence of virtually any predefined patterning influences such as morphogen gradients or mechanical cues results in an extensive heterogeneity. Moreover, the current mismatch in shape, size and lifespan between native organs and their in vitro counterparts hinders their even wider applicability. We have two openings at the PhD level to develop next-generation organoids that are assembled by guiding stem cell self-patterning through engineered microenvironments (1). One PhD project will focus on human gastrointestinal organoids (2), another one on embryonic organoids (3).

  • Brassard, J.A., Lutolf, M.P., Engineering Stem Cell Self-organization to Build Better Organoids, Cell Stem Cell, 24 (6), 860-876 (2019)
  • Gjorevski, N., Sachs, N., Manfrin, A., Giger, S., Bragina, M.E., Ordonez-Moran, P., Clevers, H., Lutolf, M.P., Designer matrices for intestinal stem cell and organoid culture, Nature, 539, 560-564 (2016)

Beccari, L., Moris, N., Girgin, M., Turner, D.A., Baillie-Johnson, P., Cossy, A.C., Lutolf, M.P., Duboule, D., Martinez Arias, A., Multi-axial self-organization properties of mouse embryonic stem cells into gastruloids, Nature, 562 (7726), 272 (2018)

We expect to hire 1 PhD students in 2020 in the area of cell-free synthetic biology / synthetic cell engineering.

Our laboratory (LBMM) develops and applies microfluidic technology with a strong translational focus. The group’s ultimate goal is to establish novel treatments against cancer.

During the past couple of years we have established powerful microfluidic platforms for cell-based and biochemical assays. We continuously develop novel microfluidic chips, detection systems and software (mainly LabVIEW) for the discovery of new drugs and antibodies, partially in collaboration with large pharma industry. Furthermore, we use microfluidic technology to predict optimal (personalised) drug cocktails for cancer therapy. The group is very interdisciplinary and includes people with various backgrounds, including biologists, engineers and programmers. However, prior knowledge in microfluidics is not mandatory for joining!

Having a comprehensive microfluidic toolbox at hand (and expanding it continuously), we are now focusing on applications in three different research fields:

Therapeutic antibodies and T-cells: Droplet based microfluidics enables to screen a large fraction of the murine and human immune repertoire in a single experiment (e.g. El Debs et al., PNAS 2012, Chaipan et al., Cell Chemical Biology 2017, Shembekar et al., Cell Reports 2018). We are actively exploiting this for novel therapeutic approaches and have founded a biotech startup company translating our results (www.velabs-therapeutics.com).

Personalised medicine: We use microfluidic devices to test drug combinations directly on solid human tumor samples and to predict optimal therapies (e.g. Eduati et al., Nature Communications 2018). Current efforts focus on genetic and imaging-based readouts. In parallel, we are constructing next generation instruments for first clinical trials. 

Genomics: We are actively developing microfluidic modules for single-cell barcoding and sequencing. This will enable the study of the mechanisms of drug resistance in great detail.

We are looking for a student to run a multidisciplinary project at the interface of soft robotics and biophysics. The goal of the project is to develop mechanically actuated systems to understand how bacterial pathogens physically interact with their environments.

The livergutbrain axis is a physiological system specialized in fuel sensing and processing. Messenger molecules of diverse chemical composition and origin mediate cross-talks between these three organs. Our research aims to focus on this system and gain insight into the mechanisms by which nutrient-derived metabolites are sensed and integrated with the hormonal and neuronal system to coordinate overall energy utilization and homeostasis. At the subcellular level, mitochondria play a key role in mediating these responses. Understanding how these organelles are regulated is thus at the center of our research. Our lab has identified a novel liver-specific mitochondrial transporter implicated in regulating hepatic fuel utilization. We are now actively studying its function and regulation in the context of controlled energy expenditure. To reach this goal, we have recently developed and validated a liver stem cell-based organoid culture system that allows the continuous expansion and differentiation of liver organoids ex vivo. Such organoids self-organize into 3D matrigel environment and recapitulate tissue architecture and hepatic metabolic functions. These hepatic organoids are well-suited for genetic manipulation, imaging, drug screening as well as genomic/proteomic/metabolomic analysis and will allow us to investigate the functions and regulations of this mitochondrial transporter.

The Suter lab is interested in quantitative analysis of gene expression to understand how cell identities are established and maintained. The PhD project we propose aims at quantitative, biophysical characterization of the transcription factor network that controls the identity of embryonic stem cells. It will involve cutting edge approaches such as genome editing, quantitative live cell imaging and cell tracking, and single molecule imaging. This project is part of a Sinergia Consortium and will involve interdisciplinary collaboration with our partner labs experts in microfluidics and in vitro transcription factor characterization (Maerkl lab, EPFL), and computational modelling of biological networks (van Nimwegen lab, University of Basel).

We also propose a project to study the role of mitotic bookmarking in cancer stem cell self-renewal. Cancer stem cells are central to the fueling of tumorigenesis through their ability to self-renew. Over the past years, transcription factors binding to mitotic chromosomes have been suggested to play a role in the ability of stem cells to self-renew, but whether mitotic bookmarking plays a role in self-renewal of cancer stem cells is unknown. Here the candidate will explore the role of mitotic retention of oncogenic transcription factors in the ability of cancer stems cells to maintain their gene expression program over cell division. To tackle this question, the PhD candidate will learn and apply a broad set of approaches, such as live cell fluorescence microscopy, genomics approaches (ChIP-seq, CUT&RUN, ATAC-seq, RNA-seq), genome editing using CRISPR technology, optogenetics, and in vitro 3D culture and migration assays.

For more details, see web pages of the EDBB program’s potential thesis directors.