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100%, Zurich, fixed-term Prof. Dr. Sereina Riniker's group for Computational Chemistry at the Institute of Molecular Physical Science is interested in the development of methodology for classical
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Science and Engineering of ETH Zurich (located in Basel). We work at the interface of protein engineering, molecular biophysics, and synthetic biology, developing new experimental and computational
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maternity cover. The Master of Advanced Studies ETH in Management, Technology, and Economics is a long-established continuing education programme at ETH Zurich, with a strong history of management education
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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
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Computer Science, Electrical Engineering, Robotics, or related field You bring: A strong foundation in machine learning, including classification and regression, model evaluation, representation learning, and
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modeling, laboratory experiments, and theoretical analyses, we seek to link microscopic processes with the macroscopic behavior of both engineering and natural systems and develop predictive tools
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Collaborate with stakeholders in professional football Develop your own research agenda and profile Take one for the team Profile Doctoral degree in computer science, mathematics, statistics, or similar
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Master’s degree in Biomechanics, Biomedical Engineering, Computer Vision, Computer Science, Neuroscience, Health Science, Biomedicine, Physio- or Occupational Therapy, or a related field. Understanding of
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of innovative AI methods and saving millions of dollars in compute time while accelerating scientific productivity. To enhance the efficacy of AI for Science models, it is imperative to integrate simulations
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and Climate Science at ETH Zurich and the WSL-Institute for Snow and Avalanche Research SLF and will be part of the NCCR CLIM+ programme which is funded by the Swiss National Science Foundation (SNSF