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Endocrine disruptive chemicals (EDCs) are chemicals that disrupt the human endocrine system by mimicking hormones or affecting their circulating concentrations in blood. Xenobiotic metabolism is the major mechanism for detoxification but can also lead to unwanted toxic metabolites. Recently, the gut microbiome has emerged as an important site of chemical biotransformation1 that can activate xenoestrogens. Our research in quantitative toxicology thus focuses on the role of gut microbiota in generating metabolites that potentially act as EDCs and the impact of gut metabolism on quantitative toxicokinetics. For this, we apply a mixed set of experimental and computational tools such as anaerobic fermentations, LC-MS/MS, kinetic modeling and in vitro toxicology assays.
- Microbiology, Modeling and Simulation, Toxicology (incl. Clinical Toxicology)
- Master Thesis
| Low-carbon hydrogen is supposed to play a key role in decarbonizing global economies. Low-carbon hydrogen can be generated using different energy sources, for example, using renewables; also known as ‘green’ hydrogen. Currently, there is a wide variety of literature that evaluates the cost of green hydrogen production, however, they all have their underlying methods and assumptions that have a huge influence on cost estimations. - Environmental Engineering, Environmental Impact Assessment
- Bachelor Thesis, Course Project, Internship, Master Thesis
| Building on the success of mRNA COVID vaccines, RNA lipid nanoparticles (RNA-LNPs) have emerged as a new class of drug formulations. The student will work on developing deep learning models that, when integrated with high-throughput science, can design advanced RNA-LNPs with targeted properties, including specific organ targeting and extended stability. These formulations will be crafted for treatments in areas like cancer and regenerative medicine. While large language models (LLMs) like ChatGPT are predominantly used for text-related tasks, their potential in drug discovery remains largely untapped. The student will also explore the capability of LLMs to make AI models in drug discovery more intuitive and accessible. - Artificial Intelligence and Signal and Image Processing, Computational Biology and Bioinformatics
- Master Thesis
| This master project is about designing a control algorithm for speed tracking in electric vehicles while considering the reliability of the system. - Automotive Engineering, Mechanical and Industrial Engineering, Systems Theory and Control
- Master Thesis, Semester Project
| This project suggests a supervisory control design for grid-forming (GFM) inverters, when operated in parallel with multiple grid-following (GFL) inverters in a microgrid (see Fig.1). The supervisory controller only acts on the P and Q setpoints of the GFM inverter, such that the stability of the overall network is maintained during transient responses. - Electrical Engineering, Systems Theory and Control
- Master Thesis
| Microbes such as bacteria and fungi produce a broad range of materials including polymers, biominerals, nanoparticles, antibiotics, and therapeutic proteins and peptides. Recent advances in synthetic symbiotic consortia, where more than one microbe are co-cultured, further broadened the range of microbial materials. This project aims to generate 3D functional materials by taking advantage of bioprinting and various microbes. In particular, the goal is to produce materials with ultra-high mechanical strength and toughness. Students with background knowledge in material engineering, chemistry and/or (micro)biology are highly encouraged to join this exciting project! - Biology, Chemistry, Engineering and Technology, Medical and Health Sciences
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| Evaluation of different inverter topologies and different modulation schemes using a multi-objective optimization procedure for a given target drive system. Optimization with respect to different objectives, e.g., efficiency, power density, costs. An existing toolchain provides a framework which can serve as a starting basis for your models and optimization algorithms. Analysis and validation of the design based on vehicle drive cycles.
- Electrical Engineering
- Master Thesis
| The Mahmood Lab (faisal.ai, Harvard Medical School, Brigham and Women's Hospital) seeks applications for master's students interested in developing deep learning methods for pathology image analysis. Our lab uses deep learning, data fusion, and medical image analysis to develop streamlined workflows for cancer diagnosis, prognosis, and biomarker discovery. - Artificial Intelligence and Signal and Image Processing
- Internship, Master Thesis
| The emergence of multidrug-resistant microorganisms has become a major threat to public health. In this project, we aim to understand interactions between nanoparticles and bacterial cells/biofilm and ultimately develop high-efficacy nanodrugs against bacteria/biofilm with multi-drug resistance. Students with background knowledge in material engineering, chemistry and/or (micro)biology are highly encouraged to join this exciting project! - Biology, Chemistry, Engineering and Technology, Medical and Health Sciences
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| ETH Zurich has the ambitious plan to achieve net-zero emissions by 2030. This project aims at supporting ETH Zurich's sustainability goals by improving energy scenarios and supporting current modelling work.
- Environmental Technologies
- Master Thesis
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