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relevant to this area of research e.g. computer science, applied mathematics, operations research Strong expertise in exact and/or approximated methods, meta-heuristics and/or machine learning, Proven
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proteomics approaches are also encouraged to apply. Your profile Applicants should hold a PhD in proteomics, molecular biology, biochemistry, or a related field. We are particularly interested in candidates
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outputs, including: A return-of-data blueprint Prototype participant reports An evaluated framework for future implementation Your Profile Master's degree and PhD in computational biology, bioinformatics
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world. The postdoc program is based at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna, one of Europe’s leading centres for basic biomedical research – with clinical
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Postdoc in Genetic Epidemiology – Statistical Genetics | Human Technopole, Milan Build the science that shapes the future of human health. Application closing date: 26.02.2026 Join a place where
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characterization of nucleic acids Computational model building and structure prediction Single-molecule fluorescence microscopy techniques Experience in cryo-EM structural biology of nucleic acids. Who we
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, catalysis and/or surface science. For Topic 4, candidates must have documented skills within computational modelling of atomistic processes. Experience in scientific programming, e.g. using Python, is
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combining field campaigns, laboratory analyses, and novel geophysical techniques. Who are you? You have a background in physics, engineering, geoscience or other related natural sciences. You hold a PhD in
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team on forefront science, while profiting from the international environment in the Department of Astrophysics . We have privileged access to the Austrian Scientific Computing super-computing facility
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural