 University of Zurich| Acronym | 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 blood-brain barrier (BBB) restricts drug delivery to the brain, complicating the treatment of Alzheimer's disease. Temporary and safe opening of the BBB is a critical step for improving therapeutic delivery. This project focuses on developing hardware for BBB opening under optoacoustic imaging guidance, along with algorithms for monitoring using optoacoustic and magnetic resonance imaging. Key tasks include designing a focused ultrasound transducer, developing a precise positioning system for mouse brain navigation, characterizing the setup through phantom experiments, optimizing imaging reconstruction algorithms, and participating in preclinical studies with healthy and diseased mice. - Biomedical Engineering, Interdisciplinary Engineering, Medical Physics, Neurosciences
- Master Thesis
| This project aims to advance super-resolution imaging techniques, specifically localization optoacoustic tomography (LOT), for optimal imaging of the mouse brain. LOT allows for angiographic imaging beyond the acoustic diffraction limit, enabling blood velocity measurements and oxygen saturation quantification, which enhances understanding of microvascular dynamics and disease. Key tasks include designing hardware for scanning the mouse brain, developing biocompatible particles for in vivo tracking of blood vessels, creating algorithms for accurate blood flow velocity measurement, and implementing AI-based methods for efficient super-resolution imaging. The project also involves participation in experiments with healthy and disease mice. - Artificial Intelligence and Signal and Image Processing, Biomaterials, Interdisciplinary Engineering
- Master Thesis
| 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 - Biomechanical Engineering, Clinical Engineering, Computation Theory and Mathematics, Fluidization and Fluid Mechanics, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Simulation and Modelling
- Master Thesis
| The project focuses exploiting generative AI to build synthetic numerical phantom for cardiac anatomy and function suitable for representing population variability. - Biomechanical Engineering, Information, Computing and Communication Sciences
- Master Thesis
| Scanning ion conductance microscopy (SICM) is the non-contact SPM technology to image live cells based on glass capillaries with a nanometric aperture. It applies a voltage and measures the ionic current flowing through the pipette above the sample in the buffer solution: the recorded current represents the feedback signal to measure the topography of the sample. In collaboration with Prof. Fantner at EPFL, this project aims to assemble a state of the art high-speed SICM to enable time-resolved live cell imaging. - Biomedical Engineering, Electrical and Electronic Engineering, Mechanical Engineering, Nanotechnology, Signal Processing
- ETH Zurich (ETHZ), Master Thesis
| Pemphigus vulgaris (PV) is a unique group of autoimmune diseases. Researches have demonstrated that antibody-induced disruption of Dsg3 transadhesion initiates a signaling response in basal keratinocytes followed by loss of tissue integrity. The 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 (cell topography and bioelectricity) in combination with the analysis of biochemical networks (signaling pathways and genetic circuits) is required.
Together with the University of Bern and University of Lübeck, we aim to utilize the tools to study the topography and electrophysiology (cell potential, ion channel recording, localized ion detection, charges) of HPEK cells (human primary keratinocytes cells) to unravel the signaling pathways of the disease. We utilize optical imaging (fluorescence dyes) and biosensing tools (including the state of the art hs-SICM and electrical FluidFM setup) to study HPEK cells upon desmosome disruption.
- Biology, Biomedical Engineering, Chemistry, Electrical and Electronic Engineering, Interdisciplinary Engineering, Medical and Health Sciences
- Bachelor Thesis, Lab Practice, Master Thesis, Semester Project, Summer School
| Are you passionate about combining cutting-edge proteomics and immunology to unravel the mechanisms behind human diseases? Join Prof. Christoph Messner’s lab at the Precision
Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), affiliated with
the University of Zurich.
At the Precision Proteomics Center in Davos, we develop and apply cutting-edge, mass spectrometry-based technologies to analyze clinical samples (body fluids, tissues, cells) to identify new biomarkers and disease mechanisms that will contribute to the next generation of personalized treatments. The position is available for an immediate start and will be contracted until the end of 2026, with the possibility of extension. - Biotechnology, Computational Biology and Bioinformatics
- Post-Doc Position
| This project focuses on enhancing SLAM (Simultaneous Localization and Mapping) in operating rooms using event cameras, which outperform traditional cameras in dynamic range, motion blur, and temporal resolution. By leveraging these capabilities, the project aims to develop a robust, real-time SLAM system tailored for surgical environments, addressing challenges like high-intensity lighting and head movement-induced motion blur. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis, Semester Project
| This project will be carried out in collaboration with the FHNW Institute for Sensors and Electronics
Monitoring plant health is crucial for early detection of pests, identifying anomalies, and ensuring timely interventions. While numerous sensors are available for this purpose, selecting the most effective ones and eliminating redundancy remains a challenge. Additionally, transmitting large volumes of data to the cloud is power-intensive, especially in resource-constrained environments. To address these challenges, local preprocessing is essential to reduce data load and enhance efficiency. Leveraging neuromorphic hardware provides a promising approach to achieve low-power, real-time processing for plant status monitoring. - Engineering and Technology
- Bachelor Thesis, Master Thesis, Semester Project
| Neuromorphic computing represents a cutting-edge approach to designing computational systems by mimicking the architecture and functionality of biological neurons. One of the persistent challenges in fabricating neuromorphic devices is the cross-device response variability, which is often seen as a limitation. However, biological neurons and synapses are intrinsically heterogeneous, exhibiting a wide spectrum of responses that enhance robustness and adaptability. Inspired by this, recent computational study[1] demonstrated that neural networks composed of heterogeneous neurons—without the need for plasticity—significantly outperform their homogeneous counterparts, particularly in their reliability across a range of temporal tasks.
[1] Golmohammadi et al 2024, https://arxiv.org/abs/2412.05126
[2] Zendrikov et al, 2023 10.1088/2634-4386/ace64c
- Engineering and Technology
- Master Thesis, Semester Project
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