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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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and engineers. Key Responsibilities 1. AI Model Development & Testing Assist in developing machine learning and deep learning models for medical imaging analysis. Implement and fine-tune models using
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simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical
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| Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.03.2032 Reference no.: 5115 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique
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outputs, and other scholarly measures of impact. Strong demonstrable background in machine learning including published work. Must have demonstrable experience in building AI models for directed evolution
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Computer Engineering. Level Scope: After earning a Ph.D., the next step in the academic or research career path is often a postdoc. A postdoc is a continuation of a researcher’s training that enables them
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
(as machine learning techniques, etc.). Personal characteristics In the evaluation of which candidate is best qualified for the PhD position, emphasis will be placed on education, experience and
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
"Cloud physics" (f/d/m/x) Background With the project Deepcloud, we will use the machine-learning revolution to better understand clouds and their role in the climate system. We aim to train a deep
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). Specializations in the department range from mathematical statistics, computational statistics, and machine learning to the development of statistical methods for astrophysics, ecology, economics, epidemiology
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materials, exam logistics, grading workflows, and technical support for learning platforms (e.g., Canvas), to ensure smooth instructional delivery. Coordinate the preparation and timely submission of letters