Student Projects ‒ NANOLAB ‐ EPFL

Master Internship/Thesis Project Topics

2026/2027

If interested by the any of the topics below, please contact by email the co‐supervisor with CC: to Adrian Ionescu

Co‐supervisor: Ali Gilani

Project Overview
Graphene’s exceptional properties, such as high electrical conductivity, large surface area, and atomic-scale thickness, make it ideal for biosensing applications. Functionalizing graphene with aptamers—synthetic oligonucleotides and antibody that selectively bind to cortisol, a critical stress biomarker—enables the development of a sensitive, selective, and scalable sensing platform. This project focuses on optimizing the aptamer functionalization process, characterizing the sensor’s performance, and integrating it into a hardware and software-based sensing system for real-time cortisol monitoring.

Objectives
• Functionalization: Optimize the binding of aptamers to graphene to preserve its electronic properties.
• Characterization: Analyze the graphene-aptamer interaction using Raman spectroscopy, XPS, SPR, QCM, and electrical measurements.
• Integration: Develop and test a complete hardware and software-based system for real-time cortisol sensing.

Methodology
• Conduct advanced characterization techniques (Raman, XPS, SPR, QCM) to validate aptamer functionalization.
• Analyze the electrical response of the graphene sensor to cortisol binding.
• Develop data analysis pipelines and Python-based coding solutions for sensor data interpretation.
• Collaborate on integrating the sensor platform with hardware and software systems for real-time monitoring.

Skills Acquired
Participants will gain expertise in:
• Nanotechnology and material science: Aptamer-functionalized graphene characterization.
• Bioelectronics: Sensing optimization and real-time detection.
• Characterization techniques: Raman, XPS, SPR, and QCM analysis.
• Hardware and software integration: Designing and testing sensing systems.
• Data analysis and Python coding: Developing solutions for sensor data evaluation.

Availability
• 1 Master’s Thesis: Focus on complete system development, from functionalization to integration and testing.
• 2 Semester Projects:
o Project 1: Antidbody functionalization and characterization using Raman, XPS, and QCM.
o Project 2: Electrical performance evaluation and integration of the graphene-based sensor with a hardware and software platform.

Co‐supervisor: Ali Gilani

Project requirements: basic theoretical knowledge of cleanroom fabrication and biochemistry knowledge

Main tasks: Biosensor characterization

Starting date: As soon as possible

Recommended type of project: Master project or internship.

Work breakdown: 10% theory, 20% fabrication, 70% characterization.

Contact person: Ali Gilani

Co-supervisor: Zahra Saadat

Project Overview:

Vanadium dioxide (VO₂) exhibits a reversible metal–insulator transition (MIT) near 340 K that is exceptionally sensitive to lattice strain, making it a compelling material for next-generation sensing technologies. Our recent work demonstrates that VO₂ can achieve an outstanding gauge factor of up to 534 at strain levels below 0.1%, significantly outperforming conventional silicon-based sensors (gauge factor ≈ 120).

Mechanical strain, whether applied externally (bending, uniaxial stretch), induced by lattice mismatch (epitaxial strain), or created dynamically via piezoelectric substrates – can strongly modulate the MIT temperature and alter the relative phase fractions (R vs. M1/M2). These effects result in exceptionally large and tunable resistance changes.

This project aims to develop a MEMS-based platform incorporating VO₂ microcantilevers and clamped–clamped beams to enable precise, dynamic control of the metal–insulator transition via piezoelectric actuation. The outcome will provide a versatile platform for strain-engineered phase transitions in VO₂, paving the way for highly sensitive, low-power electromechanical sensors and adaptive electronic devices.

Objectives:

Fine-tune microfabrication process parameters for VO₂ MEMS structures
Analyzing and reporting results clearly and effectively
Understanding the resonance frequency dependence on the strain field distribution

Prerequisites:

Basic knowledge of MEMS and microfabrication
Familiarity with cleanroom processes (EPFL- CMI access is a plus)
Skills in documenting experimental processes, analyzing results, and presenting findings clearly and concisely

Recommended type of project: Internship

Starting date: Feb. 2026

Co-supervisor: Damien Maillard

Why this project matters

Wearable health technologies are rapidly evolving—but reliable, real-time protein sensing remains a major challenge. Current biosensors based on non-faradaic electrochemical impedance spectroscopy (EIS) offer a powerful label-free detection approach, yet they struggle with reproducibility and sensitivity, limiting their path to real-world applications.

This project tackles these challenges head-on. You will contribute to advancing a technology that could enable continuous monitoring of biomarkers (e.g., stress, inflammation, metabolic markers) in wearable devices.

Project Objectives

The goal is to better understand and improve the detection mechanisms of non-faradaic EIS biosensors, bridging the gap between laboratory prototypes and practical, deployable systems.

You will combine theory, microfabrication, and experimental validation to uncover how these sensors truly work—and how to make them more reliable and sensitive.

What you will do

This is a hands-on, multidisciplinary project with a strong experimental component:

Explore the field (~10%)
- Conduct a targeted literature review on non-faradaic EIS biosensing and identify current limitations and opportunities.
Model the physics (~10%)
- Develop and refine electrical equivalent circuit models to describe the sensing mechanisms
Design & fabricate devices (~40%)
- Iteratively design and microfabricate electrode structures in cleanroom.
Test & validate (~30%)
- Perform measurements with different proteins to validate your models and quantify sensor performance.
Communicate your work (~10%)
- Document your results and present your findings clearly

Who we are looking for

Motivation and curiosity are key, but here are some specifics.

Required:

Basic programming skills (Python or similar)
Ability to work independently and take initiative

Nice to have:

Experience with microfabrication (e.g., cleanroom / CMi tools)
Basic knowledge of electrochemistry or biosensing
Laboratory experience (chemistry or biochemistry)

Co-supervisor: Emi Myzeqari, Prof. Adrian Ionescu

Project Overview

Xsensio SA is looking for a motivated Master’s student to contribute to the development of an innovative non-invasive measurement device for the in vivo characterization of a biomarker.

This opportunity is financially compensated.

Objectives

The student will work on the development and experimental characterization of an optical measurement system, exploring its potential for non-invasive biomarker detection and quantification in biological tissues.

Required Skills

We are looking for a student enrolled in a Master’s program at EPFL, preferably in Microengineering, Physics, Quantum, or Neuro-X with the following background:

Relevant coursework: biomedical instrumentation, biosensors, optical sensing, microtechnology, signal processing, electronics, measurement systems, or physiological systems.
Technical experience: experience with optical sensors, experimental setups, measurement instrumentation, data acquisition of biomedical devices.
Data analysis: familiarity with Python, or similar tools for processing and analysing experimental data.
Experimental skills: an strong interest in designing experiments, evaluating measurement performance, and interpreting results.
Personal qualities: driven, resourceful, takes initiative, and the ability to work independently as well as in a multidisciplinary team.

Nice-to-have Skills

Previous experience in biosensors, optical or electrochemical measurement techniques, or biomedical device development is an advantage but not a requirement.

Interested? Please send your CV and a short motivation statement to [email protected].

Co-supervisors: Tu Anh Le, Prof. Adrian Ionescu, Prof. Bruno Correia

Project Overview

Cardiac troponin I (cTnI) is a gold-standard biomarker for the diagnosis of acute myocardial infarction (AMI). In circulation, cTnI is commonly associated with cardiac troponin C (cTnC), forming the troponin I–C (cTnIC) complex.

Recent developments in lock-in capacitive biosensing have demonstrated the potential for real-time, label-free detection of cTnIC under physiological ionic-strength conditions. However, conventional antibody-based recognition layers present challenges, including their relatively large molecular size, variable binding affinity, and limited control over receptor orientation, which may affect sensor sensitivity and reproducibility.

This project aims to develop a compact, high-affinity protein binder targeting the cTnIC complex through de novo computational protein design. The designed binders will be experimentally validated and integrated into a lock-in capacitive biosensing platform, with the goal of improving detection sensitivity, selectivity, and the limit of detection.

Objectives

Design novel protein binders targeting selected epitopes of the cTnIC complex using de novo computational protein design.
Optimize binder candidates for high binding affinity, selectivity, and structural stability.
Experimentally characterize binder–cTnIC interactions, including binding affinity and kinetics.
Develop controlled immobilization strategies for integrating designed binders onto gold surface.
Evaluate binder-based recognition layers using SPR, and lock-in capacitive sensor.

Methodology

Computational protein design: Generate candidate binders using structure-based computational design tools, with selected epitopes on the cTnIC complex.
Protein production and purification: Express, purify, and characterize selected binder candidates.
Biochemical validation: Determine binding affinity, kinetics, and specificity using SPR and complementary protein-binding assays.
Surface functionalization: Immobilize validated binders onto metal electrode surfaces using suitable surface chemistries, with attention to receptor orientation, density, and antifouling properties.
Lock-in capacitive biosensing: Evaluate binding-induced changes in effective interfacial capacitance through phase-sensitive electrical measurements using a lock-in amplifier.

Required Skills

Strong motivation and interest in protein engineering, biosensors, and interdisciplinary research.
Basic theoretical knowledge of protein structure, biochemistry, and molecular interactions.
Good problem-solving skills and the ability to work independently within a collaborative research environment.

Nice-to-have Skills

Computational protein design: Familiarity with protein structure prediction, molecular modeling tools.
Biochemistry: Protein expression, purification, and protein–protein interaction assays.
Biophysical characterization: SPR, BLI, or related techniques.
Biosensing: Surface functionalization, capacitive sensing, impedance spectroscopy, or lock-in amplifier measurements.

This project is primarily addressed to Life Sciences (SV), Molecular and Biological Chemistry, Biotechnology, and Computational Science students, but is also open to Materials Science and Engineering and Chemical Engineering students with a strong interest in protein design and biosensing.

Contact: [email protected]