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novel manufacturing techniques is the key to improved heat transfer mechanisms and more efficient use of energy. Approximately 25 colleagues work in the division, including 15 PhD students
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, development of chemical process solutions for repurposing of electrodes, and integration of AI-based vision and active machine learning to optimize the efficiency of the process. Writing publications and
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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
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and free-energy calculations in explicit solvent. The postdoctoral researcher will employ machine-learning-accelerated methods throughout the workflow, contribute to the development of new computational
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materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
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software related to the medical field Experience of specific software and programming languages, specifically ones suitable for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and
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disease through advanced imaging and biophysical approaches. The research group hosting this position studies Contractile Injection Systems (CIS) — natural protein machines used by bacteria to deliver
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Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may also include technique development
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Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may also include technique development
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fellow devotes most of their time to research. There is the possibility of teaching up to 20%. Requirements Requirements PhD degree in in machine learning, automatic control, system identification, signal