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experimental chemistry, providing a supportive research environment. Applicants should have a PhD in Chemistry or related field, and extensive experience in python programming and machine learning models
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an
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completed, or be close to completing, a PhD/DPhil in a relevant quantitative field together with a demonstrable track record in studying humans and machine learning models. Advanced programming and
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will work as a member of an interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine
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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine their antibiotic resistance. Your work will
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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Samuel Kaski’s research group Probabilistic Machine Learning is searching for postdocs to work on AI fundamentals in exciting projects. The work includes collaboration with ELLIS Institute Finland
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the next generation of PV technologies for beyond 2030. The new postdoctoral research position will use materials modelling techniques (DFT, molecular dynamics, machine learning potentials) to investigate
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involve directed evolution and protein optimisation, applying molecular biology and biophysics. Researchers will be supported to develop skills in the latest AI or machine learning tools for protein design