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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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of agentic behaviour and publishing high-impact research. Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background
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screening (XChem), PDB deposition and biophysical techniques including SPR, DSF and NMR. Applicants must hold a PhD in Biochemistry/ Biophysics / Chemical Crystallography or a related field (or have submitted
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no.: 4520 Among the many reasons to research and teach at the University of Vienna there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as
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backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate closely with experimental scientists and contribute
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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successful in this role, we are looking for candidates to have the following skills & experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation
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46 Faculty of Philosophy and Education Working hours: 20 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: permanent Reference no.: 4367 Explore and teach