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of this project will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The doctoral student position we
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valuable hands-on experience and learn important skills for their future. This is why we’ve created an ecosystem where students (Bachelor, Master, and Doctoral students) are encouraged to ideate, build
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applicants). Experience in complementary fields such as computational modelling, bioelectronics, or materials engineering is advantageous, as is a willingness to acquire new interdisciplinary skills
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master’s degree preferably in Computer Science, Information Technology, Information Systems, Statistics, Data Science, Engineering, or a related field Strong machine learning and programming experience with
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open architecture is geared towards interdisciplinary research to promote innovation, research translation, and increase impact. The facility houses rapid prototyping machines, exoskeletons, instrumented
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, such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits chevron_right Working, teaching and research at ETH Zurich We
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-cultural. EPFL covers a wide spectrum of science and engineering and offers a fertile sSchool of Basic Sciences include theoretical and experimental biophysics, biological imaging and physics of machine
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machine learning principles. The project aims at training and learning using both bottom-up and top-down approaches with applications to cardiac image synthesis, reconstruction and classification
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that integrate machine learning with energy system optimization to make such policy optimization possible. The analysis will include policies for EV adoption, EV charging infrastructure, and electricity pricing
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100%, Zurich, fixed-term We are seeking a skilled Machine Learning Engineer to join our dynamic team. The ideal candidate will be involved in the development, optimization, and maintenance of our