 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 aim of this project is to segment aortic centrelines from low-resolution MRI data to improve automatic slice planning.
- Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences
- Bachelor Thesis, Semester Project
| This project focuses on developing robust reinforcement learning controllers for agile drone navigation using adaptive curricula. Commonly, these controllers are trained with a static, pre-defined curriculum. The goal is to develop a dynamic, adaptive curriculum that evolves online based on the agents' performance to increase the robustness of the controllers. - Engineering and Technology
- Master Thesis, Semester Project
| Approximately 1 out of 8 men worldwide will be diagnosed with prostate cancer (PCa) during their lifetime, making PCa the leading tumor type in male cancer patients. Localized PCa has a very high survival rate in patients. However, this survival rate sharply drops after the onset of metastasis, which is also the primary cause of mortality in PCa patients. Fascinatingly, in various tumor models, the primary tumor actively alters the microenvironment of distant organs beforehand, preparing a favorable niche for disseminated circulating tumor cells (CTCs) to graft and colonize with greater ease once they are in circulation. These hospitable microenvironments are termed pre-metastatic niches (PMNs) and are critical for overt metastasis formation. At present, PMN generation and its implications in PCa are poorly understood. Therefore, investigating how the PCa PMN unfolds will give us a deeper understanding of the biology of metastasis and lead to the discovery of novel drug targets essential for tailoring treatments for patients at higher risk of PCa metastasis and reducing tumor-related mortality.
Hence, in this project, students will aim to work on a series of in vivo experiments to help establish a preclinical model of metastasis formation in PCa. Primary work will include assistance with animal experiments (subcutaneous and intravenously injected tumors). Experience with extracellular vesicle isolation, Flow cytometry, PCRs, Simple Westerns, and CRISPR-CAS9 molecular editing will come with the project. - Biology, Medical and Health Sciences
- Master Thesis
| The aim of this project is to develop an automatic approach using physics-informed neural networks to infer hemodynamic parameters and flow quantities of in-silico aortic stenosis patients. - Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences
- Bachelor Thesis, Master Thesis, Semester Project
| Do you want to combine state-of-the-art machine learning algorithms with an important and life-saving treatment? Are you motivated to work with interesting real-world data and excited to implement and apply machine learning algorithms? We are currently looking for Master students in the intersection of machine learning and medicine.
- Biology, Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences, Medical and Health Sciences
- Master Thesis, Semester Project
| Do you want to combine state-of-the-art deep learning approaches with probabilistic models applied to an important domain that affects all of us? Are you motivated to work with challenging real-world data and excited to implement algorithms that have the power to generate something new? - Engineering and Technology, Information, Computing and Communication Sciences, Mathematical Sciences, Medical and Health Sciences
- Master Thesis, Semester Project
| Drug synergy is a phenomenon where the combined effect of two drugs is greater than the sum of their individual effects. While a vast amount of data exists for single drug effects on cell lines, there is a scarcity of data for drug synergy due to the huge number of possible drug combinations. Therefore, there is growing interest in employing computational methods to predict drug synergy for untested drug pairs. Our project focuses on the development of machine learning models, including graph neural networks, to forecast the synergy between any two drugs when applied to a specific cell line.
- Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition
- Master Thesis
| This project aims to investigate the use of machine learning-based algorithms to obtain a deeper understanding of the graph-structured vasculature preserved in corrosion casts. For a more detailed description, please refer to the attached document and the information below. - Central Nervous System, Computer Vision, Neural Networks, Genetic Alogrithms and Fuzzy Logic
- Lab Practice, Master Thesis, Semester Project
| The aim of this project is to develop a camera-based solution for motion correction of cerebrovascular 4D flow MRI, including hardware development and (deep learning-based) data analysis. - Biomedical Engineering, Computer Vision
- Bachelor Thesis, Master Thesis
| The aim of this project is to implement and test different T1ρ measurement approaches using MR simulations and measurements. - Biomedical Engineering, Medical Physics
- Bachelor Thesis, Semester Project
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