 University of ZurichAcronym | UZH | Homepage | http://www.uzh.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Current organization | University of Zurich | Child organizations | | Members | | Memberships | |
Open OpportunitiesThe remarkable complexity of morphogenesis and tissue regeneration implies the existence of a transcellular communication network in which individual cells sense the environment and coordinate their biological activity in time and space. To understand the fascinating ability of tissue self-organization, comprehensive study of biophysical properties (cellular nanomechanics such as tension forces and bioelectromagnetics) in combination with the analysis of biochemical networks (signaling pathways and genetic circuits) is required.
In this framework we are investigating the unacknowledged key role of Desmoglein 3 (Dsg3) as a receptor involved in mechanosensing, capable of initiating a signaling response in the transcellular communication network, which results in stem cell fate conversion, plasticity and tissue repair.
Our goal is to apply innovative Fluidic Force Microscopy to measure altered biophysical parameters upon disruption of Dsg3 transadhesion such as cell stiffness, cell-cell adhesion, cell surface charges and electric potentials. Together with the University of Bern and University of Lübeck we are further investigating how these biophysical changes relate to transcriptomic, epigenomic and proteomic response circuits to ultimately infer biophysical and biochemical circuits involved in Dsg3 signaling.
- Biochemistry and Cell Biology, Biomedical Engineering, Medical and Health Sciences, Physics
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
| The remarkable complexity of morphogenesis and tissue regeneration implies the existence of a transcellular communication network in which individual cells sense the environment and coordinate their biological activity in time and space. To understand the fascinating ability of tissue self-organization, comprehensive study of biophysical properties (cellular nanomechanics such as tension forces and bioelectromagnetics) in combination with the analysis of biochemical networks (signaling pathways and genetic circuits) is required.
In this framework we are investigating the unacknowledged key role of Desmoglein 3 (Dsg3) as a receptor involved in mechanosensing, capable of initiating a signaling response in the transcellular communication network, which results in stem cell fate conversion, plasticity and tissue repair.
Our goal is to apply innovative Fluidic Force Microscopy to measure altered biophysical parameters upon disruption of Dsg3 transadhesion such as cell stiffness, cell-cell adhesion, cell surface charges and electric potentials. Together with the University of Bern and University of Lübeck we are further investigating how these biophysical changes relate to transcriptomic, epigenomic and proteomic response circuits to ultimately infer biophysical and biochemical circuits involved in Dsg3 signaling.
- Biochemistry and Cell Biology, Biomedical Engineering, Medical and Health Sciences, Physics
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
| In this project, the student applies concepts from current advances in image generation to create artificial events from standard frames. Multiple state-of-the-art deep learning methods will be explored in the scope of this project. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| The goal of this project is to develop a shared embedding space for events and frames, enabling the training of a motor policy on simulated frames and deployment on real-world event data. - Artificial Intelligence and Signal and Image Processing
- Master Thesis, Semester Project
| This project aims at the development of a software for simulating light propagation over short distances, a necessary tool to achieve accurate measurement of oxygen saturation in tissue using compact devices. - Biomedical Engineering
- Bachelor Thesis, Master Thesis, Semester Project
| Neurocoupling is a fascinating physiological phenomenon that occurs when both arms work together in a mechanically connected task, leading to a unique state of motor control. Research has shown that during such tasks (for example when you open a bottle), electrical stimulation of one hand triggers simultaneous muscle responses in both hands. Understanding this mechanism could provide valuable insights into the role of subcortical motor pathways, particularly the reticulospinal tract, in motor control both in the healthy state and in the case of stroke, where we think there is stronger dependence on the subcortical tracts. To understand the role of the reticulospinal tracts in this mechanism, we want to test the effect of force modulation on degree of neural coupling.
We already have a device that has been specifically designed to test neurocoupling. The next step in the project would be the development (upgrade) of the software that reads out the data from the hardware, processes the data, as well as creating or improving the subject interface software. - Clinical Sciences, Human Movement and Sports Science, Neurosciences
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| The solid-state nanopore has become a powerful tool for label-free single-molecule detection, characterising DNA and RNA structures, with recent work demonstrating the ability to detect protein structure information. Studying single-cells requires us to push this protein characterisation further, with the interfacial nanopore one approach to achieving this.
In this project, you would simulate and compare with empirical data the properties of the solid-state interfacial nanopore for single-molecule detection and characterisation. - Biophysics
- Bachelor Thesis, Master Thesis, Semester Project
| Automatic failure detection is an essential topic for aerial robots as small failures can already lead to catastrophic crashes. Classical methods in fault detection typically use a system model as a reference and check that the observed system dynamics are within a certain error margin. In this project, we want to explore sequence modeling as an alternative approach that feeds all available sensor data into a neural network. The network will be pre-trained on simulation data and finetuned on real-world flight data. Such a machine learning-based approach has significant potential because neural networks are very good at picking up patterns in the data that are hidden/invisible to hand-crafted detection algorithms. - Engineering and Technology
- Master Thesis, Semester Project
| Drones are highly agile and thus ideally suited to track falling objects over longer distances. In this project, we want to explore vision-based tracking of slowly falling objects such as leaves or snowflakes. The drone should detect the object in the view of the onboard camera and issue control commands such that the object remains in the center of the field of view. The problem is challenging from a control point of view, as a drone can not accelerate downwards and thus has minimal control authority. At the same time, the perception pipeline must cope with tracking an object that can arbitrarily rotate during the fall. - Engineering and Technology
- Master Thesis
| When drones are operated in industrial environments, they are often flown in close proximity to large structures, such as bridges, buildings or ballast tanks. In those applications, the interactions of the induced flow produced by the drone’s propellers with the surrounding structures are significant and pose challenges to the stability and control of the vehicle.
A common methodology to measure the airflow is particle image velocimetry (PIV). Here, smoke and small particles suspended in the surrounding air are tracked to estimate the flow field. In this project, we aim to leverage the high temporal resolution of event cameras to perform smoke-PIV, overcoming the main limitation of frame-based cameras in PIV setups.
Applicants should have a strong background in machine learning and programming with Python/C++. Experience in fluid mechanics is beneficial but not a hard requirement. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
|
|