Super paramagnetic manipulation of nanowires for engineered strain sensors used in biomedical implants.
Stretchable Electronics, currently being used in biomedical engineering makes use of elastomers and different conductive fillers. This combination enables the creation of strain sensors which can be implanted inside of the human body. Manipulation of the fillers will allow novel sensors.
Mapping of biomolecule excretions next to cells using AFM integrated nanopores
Proteins, ions, and other excretions secreted from single cells are the key signaling factors to determine the interaction of cells with the extracellular matrix and the neighboring cells. We integrated a nanopore into an atomic force microscope (AFM) for sensing secreted molecules.
DNA Aptamer-Based Electronic/Plasmonic Biosensors
Integrating DNA-based biorecognition elements termed aptamers that recognize chemical targets with high specificity and selectivity into next-generation electronic/plasmonic biosensors.
Improved machining control with machine learning
The combination of model predictive control and gaussian processes will be experimentally evaluated to demonstrate better precision in following a contour path.
Multi-Echo Proton Spectroscopic Imaging to Map Cardiac Metabolite Levels
While MRI provides anatomical and functional information, magnetic resonance spectroscopy (MRS) allows to obtain biochemical information about substrate utilization and energy status of the heart. Multi-echo spectroscopic imaging can be used to map cardiac triglyceride and creatine levels.
Development of a MRI compatible DC-DC converter
Develop an MRI compatible DC-DC power converter. Electronics inside the MRI scanner are affected by the very strong background field, strong switching gradients and kW of RF power. The envisioned DC-DC converter should be immune to this harsh electromagnetic environment and shall not disturb the MRI
Master Thesis / 2nd Semester Project: Image-based Indoor Navigation
Many people rely on mobile navigation applications when they are visiting a new area. Such applications, however, fail to deliver the same service for indoor environments. This is mostly due to the attenuation of GPS signals inside buildings. We aim to replace GPS with image-based localization.
Fully Biocompatible conductive fibers for one-dimensional implantable biomechanical sensing system
Healthcare is one of most important issues for modern societies as global age demographics shift, particularly as the proportion of people over 65 rises to near 17% by 2050. In the last couple of years, stretchable electronics became more and more popular in medical devices. While the existing 2D stretchable sensor systems are not easily applicable to the various curved surfaces in vivo, the fiber-shaped electronic device is suturable which dramatically improves its suitability for various (bio)medical problems. The aim of this project is to develop a fully biocompatible and highly conductive fiber, which can be used for wireless and implantable biomechanical sensing systems in biomedical applications. The developed implantable systems will be applied to continuously monitor various bio-mechanical signals such as strains on ligaments, blood pressure, and flow in medical area and sportbiomechanics.
There is a growing need for non-invasive clinical imaging modalities covering large volumes of the human body accurately and rapidly for disease diagnosis and treatment monitoring. Optoacoustic tomography (OAT) images human tissue, particularly important vasculature structures, in a non-invasive, real-time and volumetric (3D) manner [1].
Transfer learning techniques for application of deep neural networks in 3D fluorescent microscopy images
Application of deep neural networks to 3D fluorescent microscopy datasets poses some specific challenges such as differences in their input distributions or scarce labeled data. We aim to address them by investigating transfer learning techniques such as domain adaptation of multi-task learning.
Automated 3D registration between optoacoustic tomography and magnetic resonance imaging
The objective of this study is to further develop an algorithm for 3D image registration between MRI and optoacoustic imaging, to streamline and automatize the registration processes for imaging in animal models.
Machine Learning for Advanced Magnetic Resonance Perfusion Quantification
Magnetic Resonance (MR) perfusion imaging is a clinically established technique to detect coronary artery disease by visual assessment. However, quantitative evaluation of myocardial blood flow is desirable as it promotes objective diagnosis. Here, ML may help to avoid expensive fitting procedures.
Data-driven inverse polynomial stochastic optimal control with applications to autonomous quadcopter flight
This project considers discrete-time Markov decision process and addresses the inverse problem of inferring a cost function from observed optimal behavior. The proposed method will avoid solving repeatedly the forward problem and its relevance will be illustrated on the quadcopter flight problem.
“Off-road” MRI - magnetic resonance imaging under harsh eddy current conditions.
A master project for a student of physics, electrical engineering or computer science involving experimental, theoretical and programming work in the domain of ultra-fast magnetic resonance imaging technology.
Machine Learning in Stroke Imaging
The objective of this project is to develop and implement various machine learning methods to the recognition, segmentation, and diagnosis of brain strokes, using a large database of computer tomographic (CT) and magnetic resonance (MR) images.
Simulation of coating processes for next gen lithium ion batteries
CFD modeling of electrode manufacturing for lithium ion batteries
Magnetic resonance thermometry for efficient CO2 capture reactors
Carbon capture and storage is anticipated to play a vital role in mitigating greenhouse gas emissions to the atmosphere. In this Master's project you will design a temperature-controlled model reactor that you will then image using a full-body human magnetic resonance imaging scanner.
Text Embeddings Optimized for Distance Computations
The goal of this project is to develop new methods for representation learning of documents and sentences, that are trained to approximate the distance between two documents.
From Prose to Rhyme: Automatic Synthesis of Rap Lyrics
This project explores automatic generation of song lyrics from different types of free form text, such as news articles or short stories.
Implementation and application of a thermal conductivity setup for nanocrystal thin films
In this project a setup should be implemented to measure the thermal conductivity in thin-films. This includes sample microfabrication, understanding and improving the setup and extending it to nanocrystal films.
Immobilization of Giant Lipid Vesicles for AFM-based Biophysical Membrane Measurements
- Establish an experimental system for force-controlled measurements in between phospholipid bilayer membranes. - Use microfabrication techniques to immobilize giant lipid vesicles on a surface. - Use a combination of atomic force microscopy and microfluidics to bring giant lipid vesicles in contact
Postprocessing techniques in acoustic resolution optoacoustic microscopy applied to human and murine skin
Acoustic resolution-optoacoustic microscopy (AR_OAM) images human and murine skin at good lateral resolutions and high depths. Applying appropriate postprocessing techniques to AR-OAM holds promise for improved skin imaging.
Development of a Fiber-Based Optoacoustic Microscope
Optoacoustic microscopy can image vasculature with single capillary resolution in 3D and at depth. This new imaging approach holds great potential to provide better insights into cerebrovascular function and facilitate efficient studies into neurological and vascular abnormalities of the brain.
Advanced image reconstruction and post-processing for optoacoustic and ultrasound biomicroscopy
Optoacoustic biomicroscopy is emerging as a promissing tool to look at the brain of small animals with high resolution. Current image reconstruction methods are limited and more advanced methods are required to unleash all the potential of this neuroimaging technique.
Biomedical Software Engineering - focusing on Continuous Integration, Distribution, and Linux Dependency Management
We develop Python-based Open Source pipelines which enable cutting-edge modelling and visualization of functional brain imaging data. As our pipelines grow in scope, we are looking to meet more stringent software engineering standards, and improve our distribution model with regard to accessibility.
Applying a new Li ion diffusion measurement technique for Li ion battery materials
A very important task in Li ion battery technologies is the ability to charge a battery fast. A limiting parameter is the Li ion diffusion of the active particles. This projects aims to develop a method to calculate the diffusion coefficient of cathode materials based on the chemical delithiation.
Sensor Fusion with Visual Motion Tracking for Airborne Wind Energy Systems
The goal of this master thesis is to develop and implement a sensor fusion scheme for AWE systems which combines measurements from the visual tracking system with onboard inertial measurements, GPS and possibly other sensors.
Cardiac Magnetic Resonance Image Reconstruction Using Machine Learning
Dynamic Magnetic Resonance (MR) imaging offers exquisite views of cardiac anatomy and function. The objective of this project is to develop and implement methods that allow learning a data model from large sets of training data to be used in nonlinear data recovery from highly undersampled MR data.
Using cardiac Diffusion Tensor Imaging data for patient-specific modelling of the heart
The aim of this project is to implement an automatic identification and delineation pipeline of the right ventricle and to parameterize and map microstructural information from MRI data onto a Finite Element (FE) model.
Development of a multi-channel Transmit/ Receive Volume Coil (Antenna) for in vivo Magnetic Resonance Imaging with Zero Echo Time
Design and test a multi-channel transmit/ receive volume coil for in vivo zero echo time (ZTE) magnetic resonance (MR) imaging on a human scanner.
Diffusion Tensor Imaging of the Human Heart
Diffusion tensor imaging (DTI) is a non-invasive Magnetic Resonance Imaging (MRI) technique to probe the cardiac muscle fiber orientation. The ability of DTI to image the complex cardiac fiber architecture is a promising tool for assessing cardiac function in patients suffering from cardiomyopathy.
Biophysical characterization of the subdural local field potentials in mouse neocortex and fabricating low-impedance flexible electrode arrays
We are seeking a student who is interested in fabricating flexible electrode arrays and analyze the data collected by these arrays to quantitatively analyze the sources of the local field potentials recorded by these electrode arrays from the surface of the brain.
Fabrication of flexible shank-electrodes for long-term multi-area electrophysiological recordings in the prefrontal areas of behaving rats
We are looking for a student who will establish a reliable recipe for the fabrication and assembly of minimally-invasive and flexible electrode shanks that will be used for recordings from the prefrontal areas of awake behaving rats in decision-making paradigms for brain machine interfaces.
Q-learning using generalized Benders decomposition
This project, at the interface between control theory and machine learning, develops advanced algorithms and accompanying theory for solving non-convex control problems using generalized Benders cuts. This will extend recent theoretical and algorithmic results, primarily to hybrid systems.
Set-up and testing of an adaptive optics imager for the Swiss 1.2m telescope in La Silla, Chile
The department of astronomy of the University of Geneva is building a new imager for the characterization exoplanets and their host stars. This new instrument fill benefit form an adaptive optics system featuring a deformable mirror with 140 actuators using a micro-opto-electro-mechanical system.
Electronic processing of quantum random numbers from a photonic chip
The goal of this project is to develop a complete interface, control and processing electronic system based on state-of-the-art FPGA technologies to integrate the optics with current IT systems.
Automated identification of two-dimensional crystals based on optical contrast difference
The goal of this project is to develop an automated setup that is able to identify flakes of different thicknesses on Si/SiO2 substrates by analyzing the difference in optical contrast between the crystals and the substrate.
Optimal State Estimation of a Levitated Nanoparticle
In this project, a Kalman filter will be implemented to estimate the time-varying state of a nanoparticle held in the focus of a laser beam. The state of the particle will then be used in a feedback loop to act back on the particle and to provide ultimate control over the nanoparticle's dynamics.
Development of an optical fiber network for signals with correlated noise
In this project an optical fiber network comprising n optical fibers will be developed. The objective is to study the influence of correlated noise on the output signals gi(t).
Emergence of Global Leader-Follower Structure via Local Social Interactions
Most mathematical models of influence processes in social groups focus on how the underlying social network structure shapes the opinion evolution. This project studies the opposite direction: how certain network structures emerge from opinion exchanges.
Behavior Identification in Dynamical Social Networks
Social network topologies emerge as the results of actor's linking decisions. Based on their behavior, individuals strategically decide their own set of relationships to optimize their network positions. In this project, we want to validate our novel game-theoretical approach on real-world data.
Feedback stabilization of a micro droplet in an optical trap
The project consists of building an optical trap and conducting position measure- ments of the droplet as a function of laser power. In a second step, a PID feedback loop will be implemented to actively stabilize the trap.
Development of a reflection-type near-field optical microscope
In this project a reflection-type near-field optical microscope will be designed, developed and characterized.
Automated nanoparticle loading
Levitation optomechanics systems consist of a nanoparticle that is optically trapped and levitated by a focused laser beam under vacuum conditions. The aim of this project is to design and build a reliable and automated nanoparticle loading process that can be triggered remotely.

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