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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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Science About the project This PhD project integrates pharmacoepidemiology, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies
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computational sub-team that includes computer scientists and computational PhD students, fostering an interactive environment of technical exchange, code review, mutual support, and collaborative problem-solving
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to staff position within a Research Infrastructure? No Offer Description PhD Position in Physics-Informed Machine Learning for Cardiac Magnetic Resonance The CMR Zurich group at the Institute
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scientists, and technology innovators. Located in the heart of Las Vegas, the College serves a diverse student population and offers robust programs in electrical and computer engineering, computer
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Programming experience (e.g., R, Python) and interest in machine learning approaches Doctoral degree (PhD or equivalent) in Education, Psychology, or a closely related field by the start date Knowledge, Skills
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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Functional Theory (DFT), machine-learned force fields (MLFF), graph neural networks (GNNs), or large language models (LLMs). Extensive Knowledge In: • First-principles atomistic simulations with packages
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strong AI focus; a PhD is desirable, but not mandatory Advanced knowledge of machine learning, statistical modeling, and modern AI methodologies Strong programming skills, preferably in Python and common
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infrastructure (e.g. Observatorio del Roque de los Muchachos) Hands-on training in cutting-edge techniques, from detector R&D to advanced data analysis and machine learning. Attendance to international