379 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" uni jobs in Sweden
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advantage Are curious and motivated to learn Contract terms Temporary employment with a start date as soon as possible, ending end of August. What we offer Chalmers provides a cultivating and inspiring
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developing and implementing data management for human data to meet future needs within data-driven Life Science research. More information about NBIS can be found at https://nbis.se . Duties We are looking
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equipment used by multiple researchers (e.g., DNA and RNA extraction rooms, PCR machines, instruments to measure concentration and integrity of nucleic acids, and knowledge of best practices for down-stream
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, or quantum-inspired methods Experience with hybrid quantum–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience
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, such as pulse design or numerical optimization Background in data-driven or machine-learning approaches relevant to optimal control (e.g., model learning, reinforcement learning) What you will do Take
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Dopson, mark.dopson@lnu.se , +46-(0) 480-447334 HR partner: Marianne Palmér, marianne.palmer@lnu.se Want to know more about the research environment Eemis in biology? Check out Lnu.se https://lnu.se/en
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Eemis in biology? Check out Lnu.se https://lnu.se/en/research/research-groups/linnaeus-university-centre-for-ecology-and-evolution-in-microbial-model-systems/ Welcome with your application no later than
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who have experience in robotics and Reinforcement Learning to work in projects with a focus on: Designing satellite position controllers using reinforcement learning Where the student's expertise and
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Technology and learning Teacher
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optical microcavities, and similar lines, summarized in these publications: https://www.pnas.org/doi/abs/10.1073/pnas.2505144122 https://www.science.org/doi/full/10.1126/sciadv.adn1825 https