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design, and/or machine learning in the context of integrated photonics. We are looking for someone who wishes to work theoretically in this field, while still maintaining close contact with experiments
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groups working towards a common goal. For this postdoc project, we seek a dynamic and motivated candidate with an interest in computational electromagnetism, inverse design, and/or machine learning in
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problems through research, collaboration and education on sustainable plant production. We teach and research about plants for food, feed and energy. The research and teaching focus on the production
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the Division of Data Science and Artificial Intelligence and the employment is with Chalmers University of Technology. The division’s research spans from foundational machine learning theory to applications
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. Participate in regular project meetings and collaborate closely with other members of the research group. Author scientific articles, both independently and collaboratively. Teach up to 20% of your working time
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intelligence, machine learning, data science, applied mathematics, or a closely related field, awarded no more than three years prior to the application deadline*. Documented research experience in machine
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description and duties The postdoc fellow will conduct research at the borderline between the fields of information visualization / visual analytics as well as machine learning in close collaboration with
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measurement and control platform for optimal island operation of Chalmers’ wind-battery system. Machine learning-based forecasting tools for renewable production using limited local measurement data
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for three weeks of training in higher education teaching and learning. These tasks will be performed: Analysis of time series of active fire and burned area data together with ancillary datasets (e.g. biomass
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are looking for The following requirements are mandatory: To qualify for the position of postdoc, you must hold a doctoral degree in computer science, artificial intelligence, machine learning, data science