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system design. We employ advanced computational methods, machine learning, modeling, and custom hardware and software to continually test our solutions in various real-world industry projects. In one
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research agenda to develop safe and effective measures to curb harmful online content and strengthen public discourse. As part of our efforts, we are using state-of-the-art machine learning techniques and
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experience CH/EU/EFTA citizenship or a valid Swiss work permit Master’s degree (ETH, university) in engineering, mechatronics, computer science, or a related field Experience in machine learning, signal
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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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to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, Villigen), the SDSC provides expertise and services to various
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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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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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science journey, from the collection and management of data to machine learning, AI, and industrialization. The Center comprises a multi-disciplinary team of data and computer scientists and experts in
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of machine learning and optimization methods in manufacturing. We aim to create intelligent systems for process parameter selection, condition-based maintenance, and human-machine interaction. Job description
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Publication list Contact details of two refereesPlease send your application to [nicola.serra+sinergia@uzh.ch]. Further information about [Department of Mathematical Modeling and Machine Learning or Department