Hochschulmedizin ZürichAcronym | HMZ | Homepage | http://www.hochschulmedizin.uzh.ch/ | Country | Switzerland | ZIP, City | 8001 Zürich | Address | Künstlergasse 15 | Phone | +41 44 634 57 37 | Type | Alliance | Current organization | Hochschulmedizin Zürich | Child organizations | | Members | |
Open OpportunitiesDirect Air Capture (DAC) of carbon dioxide (CO2) is a promising technology to combat climate change by removing CO2 directly from the atmosphere. One approach to DAC involves the accelerated weathering of calcium hydroxide (Ca(OH)2), a process where CO2 exothermically reacts with Ca(OH)2 to form calcium carbonate (CaCO3) and water. A two-step regeneration allows for a cyclic process. In the first regeneration step, CaCO3 is sent into a high-temperature reactor. Inside this reactor, the CaCO3 decomposes into calcium oxide (CaO) and CO2 at temperatures near 900 ºC at atmospheric conditions. The calcium oxide is then hydrated in the second stage to form Ca(OH)2. The hydration reaction is exothermic and presents a suitable opportunity for heat recovery. The resulting Ca(OH)2 is newly used as the sorbent material in the capture step.
Understanding the behavior and sensitivity of this process to key operating conditions is crucial for optimizing its performance and energy efficiency. Moreover, the influence of water on the porous calcium oxide (CaO) sorbent material for CO2 adsorption represents a crucial aspect of process optimization.
- Process Control and Simulation
- ETH Zurich (ETHZ), Master Thesis
| In this project, you will investigate the use of event-based cameras for vision-based landing on celestial bodies such as Mars or the Moon. - Engineering and Technology
- Master Thesis, Semester Project
| The Swiss watch industry focuses on perfectioning their capabilities since its beginnings. The use of printable, protective elements during surface finishing processes would allow for a new level of resolution and complexity. Nevertheless, currently used materials are not printable due to their high viscosity and are often hard to remove. We therefore are developing a printable polymeric coating that allows for traceless removal with water. - Chemical Engineering, Colloid and Surface Chemistry, Industrial Chemistry, Macromolecular Chemistry, Manufacturing Engineering, Mechanical Engineering, Polymers
- Bachelor Thesis, ETH Zurich (ETHZ), Master Thesis, Semester Project
| Despite the growing amount of work on applying causal discovery method with expert knowledge to areas of interest, few of them inspect the uncertainty of expert knowledge (what if the expert goes wrong?). This is highly important since that in scientific fields, causal discovery with expert knowledge should be cautious and an approach taking expert uncertainty into account will be more robust to potential bias induced by individuals. Therefore, we aim to develop an iterative causal discovery method with experts in the loop to enable continual interaction and calibration between experts and data.
Based on the qualifications of the candidates, we can arrange a subsidy/allowance for covering traveling or living costs. - Expert Systems, Health Information Systems (incl. Surveillance), Statistics
- Internship, Master Thesis, Semester Project
| This project focuses on developing an explainable Artificial Intelligence (xAI) framework based on graphical modeling (GM), to enhance the capacity and capability of medical AI. Collaborating with the Swiss Paraplegic Centre (SPZ) for validation, our goal is to improve the long-term prognosis of spinal cord injury (SCI) individuals. Through medical records and a multimodal sensory monitoring system, we aim to create digital twins capable of integrating diverse data sources, guiding medical treatment, and addressing common secondary health conditions in the SCI population. The envisioned GM-based digital twin (GMDT) will represent hierarchical relations across demographic features, functional abilities, daily activities, and health conditions for SCI individuals, allowing for downstream tasks such as prediction, causal inference, and counterfactual reasoning. The assimilation and evolution between the physical and digital twins will be implemented under the GM framework, promising advancements in personalized healthcare strategies and improved outcomes for SCI people. Please refer to the attached document for more details about the task description. Based on the candidate's qualifications, funding/allowance can be provided. - Biomedical Engineering, Digital Systems, Knowledge Representation and Machine Learning, Pattern Recognition, Simulation and Modelling
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| Understanding knee kinematics is a key requirement for understanding the processes occurring during injury or pathology as well as their remedies. Compared to optical systems, x-ray fluoroscopy directly measures the joint kinematics without soft-tissue artifacts and is thus the method of choice whenever such high performance is required.
To extract the 3D knee kinematics the rendering of each bone (3D geometry acquired independently by e.g. CT) is matched to the x-ray image in a process called 2D-3D pose estimation or 'image registration'. Current manual pose-estimation methods are time-consuming, expensive, and prone to operator bias. For example, a 10-second trial measurement acquired at 30 Hz consists of about 300 images and takes an experienced operator about 1500 minutes to match manually.
Since most studies often consist of thousands of images, an automated way of performing pose estimation to assist or replace manual alignment becomes crucial.
- Biomedical Engineering, Image Processing
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| The process of evaluating sleep examinations and diagnosing sleep disorders through polysomnographies (PSGs) is labor-intensive as it requires manual analysis from sleep technicians and doctors. In collaboration with Clinic Barmelweid, a leading sleep and rehabilitation clinic in northwestern Switzerland, we plan to automate this process using machine learning models. Clinic Barmelweid conducts approximately 400-450 PSGs annually and has access to a dataset of more than 5,000 recordings. - Artificial Intelligence and Signal and Image Processing, Biomedical Engineering, Medical and Health Sciences
- Collaboration, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| Pulmonary hypertension (PH) in newborns poses significant diagnostic challenges due to its association with various diseases and its impact on morbidity and mortality. Early and accurate detection is essential for effective management, yet current manual echocardiographic assessment is time-consuming and requires expertise. This project aims to develop an automated machine learning method using multimodal variational autoencoders (VAEs) and diffusion models to predict PH in newborns from ultrasound, ECG data, and clinical variables. Leveraging a cohort of 270 newborns from the University Children’s Hospital Regensburg, the project will enhance interpretability and feature representation by assessing the significance of each data type and utilizing synthetic data augmentation. The hybrid approach of combining VAEs with diffusion models is expected to improve prediction accuracy and generalization, advancing early detection and understanding of PH in newborns. - Biomedical Engineering, Computer Communications Networks, Electrical and Electronic Engineering, Image Processing, Signal Processing
- ETH Zurich (ETHZ), Master Thesis
| This Master's thesis focuses on the experimental determination of material properties for Ti6Al4V, essential for the numerical simulation of machining processes. The work involves preparing various samples, conducting flow curve tests, damage behavior analyses, and anisotropy assessments. Additionally, EBSD analysis, hardness measurements, and potentially chemical analyses will be performed. The results will be used to validate machining simulations using SPH/FEM, comparing process forces and chip formation. - Mechanical and Industrial Engineering
- ETH Zurich (ETHZ), Master Thesis
| This Master's thesis focuses on the experimental determination of material properties for stainless steel, essential for the numerical simulation of machining processes. The work involves preparing various samples, conducting flow curve tests, damage behavior analyses, and anisotropy assessments. Additionally, EBSD analysis, hardness measurements, and potentially chemical analyses will be performed. The results will be used to validate machining simulations using SPH/FEM, comparing process forces and chip formation. - Mechanical Engineering
- ETH Zurich (ETHZ), Master Thesis
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