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reactions. We welcome applicants from diverse backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate
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equations, uncertainty quantification, and machine learning. Candidates must have obtained a Ph.D. in mathematics or applied mathematics before the start date and must demonstrate research excellence, strong
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acquisition and management. This role directly builds upon Ph.D. research by applying advanced 3D imaging, algorithm design, machine learning, software engineering and visualization techniques to a real-world
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modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control
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Python, MATLAB, or C++. Experience with machine learning techniques, CAD, computational modeling, 3D printing, motion capture, and/or material testing. Proficiency in programming languages commonly used in
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Neurobiologie (ZMNH) Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI (baiome.org) to complement our lively and enthusiastic team of machine learning and
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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to scholarly peer-reviewed publications. Opportunities exist for the selected applicant to mentor students and to develop learning opportunities (courses, workshops, etc.) for the UK earth science community. The
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of Biostatistics at University of Florida and Dr. Hongkai Ji (remote) in the Department of Biostatistics at John Hopkins University. This position, available immediately, focuses on developing statistical, machine
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run