873 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" positions in Sweden
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and mixed-signal design, and thus broaden and strengthen our expertise in the design of electronic systems. You will also develop and teach courses in electronics design at the bachelor and master
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and machine learning, we collaborate globally to monitor environmental change and support a sustainable future. About the research project The postdoc will work at Chalmers University of Technology in a
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and software Experience in developing technical documentation, safety procedures, and audit reports Experience with automation technology Experience with machine safety and/or process safety systems
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researchers develop new machine learning (ML) methods to tackle challenging molecular engineering problems in life sciences and materials design. Situated in the Data Science and AI division , our group
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Advance at Chalmers. You find the full list of PIs of these research groups on the Chalmers homepage: https://www.chalmers.se/en/collaborate-with-us/collaborate-in-research-and-innovation/research-related
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, for the benefit of researchers as well as teachers and other educational professions. Read more about The Postgraduate School in Educational Sciences: https://www.umu.se/en/umea-school-of-education/education/the
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Extensive knowledge of relevant machine learning and AI techniques Self-motivated individual with ability to work independently Teaching and mentorship abilities or interests in personal development A
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Experience in machine learning Knowledge of SDN and NFV Knowledge of basic TCP/IP protocols What you will do Conduct high-impact research and publish in leading journals and conferences Shape research
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environment. For more information: https://www.nano.lu.se/facilities/lund-nano-lab We offer In this position, you will get the opportunity to work in a world class research environment with highly qualified
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/NIR) for separation and material sorting, and use machine learning for process optimisation and performance prediction from fiber to finished product. Functional processing of recycled materials and AI