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Your profile We seek candidates with an outstanding research record in deep learning, in particular in one or several of the following areas: modeling and architecture development, domain adaptation
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interdisciplinary study programmes. Candidates with background in biology, bioengineering, biotechnology or microbiology with experiences in method and technology development are welcome to apply as well
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or microbiology, with a strong interest in technology development, are welcome to apply as well. The combination of biological and technological aspects is central in our group and in this project. A possible
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. We are working closely together with ETH researchers to provide support in the wide area of scientific computing from data management and analysis, development of scientific software, to porting and
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development of algorithms and large-scale numerical simulations. Your expertise will extend to various areas, including quantum Monte Carlo, machine learning, quantum computing, quantum machine learning, and
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. 10007007; project start 01.10.2025: collaboration partners: J. Löffler, ETH Zürich; K. Klein, Universität Zürich; R. Müller, ETH Zürich, B. Schaller, Universitätsspital Bern) focusing on the development
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independent analytical work with active participation in joint project planning, interpretation, and dissemination of results. Your responsibilities will also include the development and maintenance
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experience includes primary cell culturing, work with advanced in vitro models, epithelial/endothelial barrier characterization, and iPSC differentiation; skills in optical microscopy, sensor development and
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Workplace We offer Your career with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society. We are actively
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), sorbent properties (e.g., surface charge, specific area), and solution chemistry. Through this work, we aim to support model development and inform regulatory frameworks, in close collaboration with