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, electrical engineering and computer science to design highly efficient and sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. Project background Our
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degree in physics, computer science, mathematics, computational neuroscience, or related fields. Extensive knowledge of dynamical systems theory. Excellent programming skills in Python. Previous experience
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be based either within the Department of Mechanical and Process Engineering or the Department of Mathematics at ETH Zurich, dependinhg on the candidate's background and preferences. Profile A masters
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Required experience: CH/EU/EFTA citizenship or a valid work permit for Switzerland A Master’s degree (ETH, university) in engineering, computer science, or a related field Strong academic performance meeting
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element modeling, computational fluid dynamics). Knowledge of heat and mass transport processes in heat-sensitive materials and process optimization. Experience in supply chains and hygrothermal
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selection process with applications accepted year-round. Eligibility requirements: Candidates should hold a PhD degree in computer science, data science, mathematics, physics, statistics, or electrical
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Department of Mechanical and Process Engineering/Intelligent Control Systems can be found on website . Questions regarding the position should be directed to Dr. Marianne Schmid Daners, marischm@ethz.ch
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80%-100%, Zurich, permanent ETH Zurich is one of the world’s leading universities specializing in science and technology. It is renowned for its excellent education, its cutting-edge research, and
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scientific and engineering computing, and explores commercial pathways for software innovations. If you are looking for a role that blends technical excellence, leadership, and business strategy, we would like
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research and its efforts to put new knowledge and innovations directly into practice. The Laboratory of Metal Physics and Technology (LMPT), part of the Department of Materials at ETH Zurich, conducts