Physiologically informed neural networks for cardiac Diffusion Tensor Imaging
The aim of this project is to investigate the possible improvements of parameter estimation in cDTI by training neural networks on synthetic data.
Machine and deep learning based acid-calling for next-generation protein sensors
Nanopore technology – which amongst others enabled RNA-sequencing based Corona virus detection – can be used to develop novel protein sensors, where the information extraction about the amino-acid sequence both with basic noise reduction algorithms and neural network approaches plays a crucial role.
Non-invasive glucose sensor for the preterm infants: Enhancing the membrane
The student will work on enhancing the membrane properties (mechanical strength, increase the permeability to glucose, and enhance the bond between the membrane and microfluidics chip) and establish a membrane-chip production process. This membrane also needs to fulfill medical-grade biocompatibilit
Phantoms with tunable chambers mimicking microvasculature and hemodynamic optical phenomena
The student will work on creating prototypes of silicone phantoms containing an inclusion chamber(s) with microfluidics to mimic localized hemodynamic changes. Each phantom will be designed to test diverse hemodynamic phenomenon for different NIRS modalities, e.g., fNIRS, TD-NIROT.
Robot Primate to study Imitation Learning (ETH Neurotechnology Group)
Human-level imitation learning remains to be the greatest frontier in robotics. We are interested in understanding the computations in the primate brain during imitation and would like to build a robotic avatar of a marmoset monkey, with which a real monkey can interact.
Improving optical brain imaging with Neural Network
We are looking for a highly motivated master or bachelor student, who is ready to face challenges in research and engineering. Together we will further develop NIR imaging technology for neonatal brain, namely: IMPROVE BRAIN IMAGING WITH THE HELP OF NEURAL NETWORK
Monitoring rapid changes in tissue oxygenation with time-domain near-infrared optical tomography
We are looking for a highly motivated master or bachelor student, who is ready to face challenges in research and engineering. Together we will further develop NIR imaging technology for neonatal brain, namely: MONITOR RAPID CHANGES IN TISSUE OXYGENATION WITH NIROT
Create adaptive probe for neonatal brain tomography
We are looking for a highly motivated master or bachelor student, who is ready to face challenges in research and engineering. Together we will further develop NIR imaging technology for neonatal brain, namely: CREATE ADAPTIVE PROBE FOR NIROT
Speed-up TD NIROT system
We are looking for a highly motivated master or bachelor student, who is ready to face challenges in research and engineering. Together we will further develop NIR imaging technology for neonatal brain, namely: SPEED UP THE MEASUREMENT AND INCREASE THE DYNAMIC RANGE OF THE IMAGING SYSTEM
Data analysis for single protein sensors
Technologies that allow for the sensing of single biomolecules (e.g. proteins) which are related to deseases like Alzheimers or cancer are needed to improve future research, diagnostics, and treatment. This work will allow students to deepen their knowledge in data analysis.
Multispectral Optoacoustics of Superficial Temporal Artery
This project aims to develop algorithms to reconstruct and analyze multispectral optoacoustic images from superficial temporal artery.
Startup thesis in joint ETH/Roche venture - Development of next generation biosensing/diagnostics enabled through machine learning
Lino Biotech AG, a Roche/ETH spinoff has interesting student project to offer. If you have a background in biochemistry, engineering, chemistry or physics and want to complete your thesis in a vibrant startup environment do not hesitate to contact me. We have amazing projects to offer, ranging from assay development for rare diseases, to machine learning for image processing, surface chemistry development, lithography as well as hard core optics/statistics to further work on the basis of focal molography. Just contact me and we can discuss what suits you best.
Cell-free DNA fragmentation in cancer and other diseases
We are currently looking for Master students in the field of Bioinformatics or Computational Biology for the analysis of cell-free DNA sequencing data. We have several topics which students can apply for depending on their previous expertise and proposed duration of the project (3-6 months).
The link between spread of alpha-synuclein, structural connectivity alteration and neurodegeneration in a-synuclein mouse model
Elucidating the temporal and spatial relation of alpha-synuclein accumulation related pathological changes, aberrant brain structural connectivity and neurodegeneration are important for understanding the mechanism of Parkinson’s disease.
Eyetracking Toolbox for Drone Racing Research
Eyetracking Toolbox for Drone Racing Research
Data-driven Keypoint Extractor for Event Data
Design and implement a data-driven keypoint extractor for event data.
Benchmarking Algorithms for Autonomous Drone Racing
Benchmarking Algorithms for Autonomous Drone Racing
Domain Transfer between Events and Frames
Design and implement an unsupervised domain adaption approach for transferring multiple tasks from labelled frame datasets to event data.
Low-Latency High-Bandwidth Communication for Drone Racing
Low-Latency High-Bandwidth Communication for Drone Racing
3D reconstruction with event cameras
This project will explore the application of event camera setups for scene reconstruction
Internship in Digital-Health and AI
Business development, market research We are seeking an intern for (1) performing systematic market research on clinical decision support systems (companies and their business models and pricing); (2) contributing to the development of a business plan for an envisioned spin-off company.
Efficient Asynchronous Event-based CNN Processing
Design and implement efficient asynchronous event-based networks to achieve low latency inference.
Perception Aware Model Predictive Control for Autonomous Power Line Tracking
Perception Aware Model Predictive Control (MPC) for Power Line Tracking
Open PhD position Balgrist University Hospital
Pain phenotyping in spinal disorders
Deep learning based K-wire detection
The goal is to develop a deep-learning based method to detect the 3D position of surgical wires (K-wires) from camera readings of the Microsoft HoloLens 2 and the ZED mini, respectively.
The role of PIEZO1 gain-of-function in tendon stress adaptation
Determination of tendon viscoelastic properties in PIEZO1 gain-of-function mice
Ultrasound attenuation imaging based on an observational model
Development of a framework for the inference of local ultrasound attenuation in biological tissue.
Improving Visualization of Arthroscopy using Augmented Reality (AR) Technologies
This work aims to enhance minimally invasive joint surgery with Augmented Reality (AR) technologies.
DNA-​Based Biosensing for In-​Vitro and In-​Vivo Applications
Developing the next generation of electronic biosensors to detect neurochemicals released by in vitro neuronal networks and biomarkers in clinically relevant human fluids. These novel biosensors will help us answer relevant neuroscience questions and human health concerns. The project will involve t
GPU-based Simulator for Event-Based Computer Vision
Design and implement a fast GPU-based simulator for generating low-level computer vision ground truth.
Fast TR switches for ultra high field MRI
Short T2 MRI measurements opened up new possibilities in studying essential factors related to many neurodegenerative diseases. To perform such measurements cutting edge hardware is required that overcomes current limitations. One important device is the TR switch that shall be improved on in this work.
Summer/Student Job - Production Engineer / Drone Assembly
Student/Part-time job in a drone startup. Your task is to help to build, repair and test our unique drone. We are offering flexible work hours and workload, ideally a 60-100% intro phase of 1+ months followed by on-demand/hourly based work during your studies.
Molecular Holograms for Biosensing Applications
Focal Molography is a state-of-the-art technique for label-free detection of molecular interactions in diagnostics and analytical applications. Being in transition from academia to industry, focal molography requires optimisation and scale-up of the manufacturing processes.
Development of a clinical magnetic resonance spectroscopy (MRS) protocol in spinal cord
The specific aim of this project is to implement and optimize a novel, cutting-edge MRS method in spinal cord to assess (micro-) structural changes in vivo in cervical and lumbar cord.
End-to-End Compositional Language Modeling
We are looking for a motivated student to work on the master project of end-to-end compositional language modeling. Our aim is to understand the underlying dynamics of language generation as well as the characteristics in long sequence distances.
Develop the electronics for a new medical sensor
You will work on bringing medical tests to peoples home. You will further develop the hardware and software for a readout device that can perform a variety of diagnostic tests in a reliable but simple fashion.
Development of a platform for automatic detection of spinal diseases for FE-modelling.
Development of a platform for automatic detection of spinal diseases and 3D segmentation of spinal discs.
Computational Fluid Dynamics of Blood Flow in the Aorta
The aim of this project is to investigate and characterize flow patterns in various patient-specific aortic geometries using CFD.
Developing a stretchable biohybrid brain implant for high resolution deep brain stimulation
The project aims to develop a stretchable biohybrid implant to restore vision by direct stimulation of the primary visual centers in the brain.
Research Assistant/PhD Student in Computer Science, Visual Analytics, Data Science
Open position for a PhD student in the area of multidimensional data analysis and visualization at the University of Zürich. This position is for a PhD student participating in a SNF (Swiss National Science Foundation) funded joint project between UZH and EPFL.
Fully Funded PhD Position in Multi-modal Data Analysis and Integration, Multimedia Retrieval, Semantic Web, Explainable AI and/or Data Mining
The Dynamic and Distributed Information Systems Group at the University of Zurich (Switzerland) is inviting applications for a Fully Funded PhD Position With a keen interest at least one of the following areas: Multi-modal Data Analysis and Integration, Multimedia Retrieval, Semantic Web, Explainable AI and Data Mining
Routing algorithm for accessible walking routes for people with mobility impairments. (Master thesis)
Please see the attached project call documents for details (requires UZH login)
Multi-agent Drone Racing via Self-play and Reinforcement Learning
Drone racing requires human pilots to not only complete a given race track in minimum-time, but also to compete with other pilots through strategic blocking, or to overtake opponents during extreme maneuvers. Single-player RL allows autonomous agents to achieve near-time-optimal performance in time trial racing. While being highly competitive in this setting, such training strategy can not generalize to the multi-agent scenario. An important step towards artificial general intelligence (AGI) is versatility -- the capability of discovering novel skills via self-play and self-supervised autocurriculum. In this project, we tackle multi-agent drone racing via self-play and reinforcement learning.
Development of next generation RNA delivery platform
In this project, you develop the next generation of RNA delivery platform which is aimed to overcome the limitations associated with current lipid based platforms. The project
Startup position - DNA Hybridization Studies Using Focal Molography
This project aims at comparing the performance of focal molography to the surface plasmon resonance technique. The main goal of this semester project is to obtain the kon and koff values of a well-studied DNA hybridization model and compare the values to those already obtained using SPR.
Deep reinforcement learning for collaborative aerial transportation
Collaborative object transportation using micro aerial vehicles (MAVs) is a promising drone technique. It is challenging from a control perspective, since multiple MAVs are mechanically coupled, imposing hard kinematic constraints. Traditional model-based methods often require linearization of the nonlinear problem which restrains the performance such as transporting speed and the payload. The goal of his project aims at exploring the possibility of using the deep reinforcement learning approach to obtain a centralized control policy for collaborative aerial transportation, which is more efficient than the state-of-the-art methods. The policy will be trained in a simulation environment and then transferred to real-life experiments. Applications should have strong experience in C++, Python. Applicants with reinforcement learning and flight control background are favored.
Learning implicit deep tissue structures for Near infrared optical tomography
It is a challenge to perform image reconstruction for near infrared optical tomography in real time based on conventional model-based approaches. Machine learning methods using implicit shapes have a great potential to improve NIROT image reconstruction.
In-silico cardiac and cardiovascular modelling with physics informed neural networks
The aim of the project is to investigate the benefits, requirements and drawbacks of physics informed neural networks in the context of personalised cardiac and cardiovascular models
Striving for gigaseal with force-controlled patch clamp on contracting cardiomyocyte
We aim to determine the key parameters to achieve an electric gigaseal between the cell membrane and the internal wall of a microfabricated pipette. Indeed, we are developing a force-controlled patch clamp using FluidFM to study the electrophysiology of single cells in a gentler and more controlled way.
Investigating cell mechanics with FluidFM force spectroscopy
This project aims to investigate the mechanical properties of living cells using FluidFM technique combined with novel optical tools.

Powered by  SiROP - the academic career network