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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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mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time-lapse data Proven programming expertise in
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Signal Processing and Image Analysis group (DSB), Section for Machine Learning, at IFI. DSB has seven full-time and five adjunct positions and carries out research across image analysis and machine
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deadline Experience with urban acoustic monitoring or transportation noise assessment Programming skills in Python Knowledge of machine learning techniques applied to acoustic or environmental data
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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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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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goals and those of faculty mentor; and publication of research findings/scholarship during postdoc appointment period. Projects in the Rocha lab address the evolutionary history of populations and species
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machine learning are encouraged to apply. The postdoc will also play a leading role in co-mentoring graduate and undergraduate students, assist in organizing seminars and activities related to RTG
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The Franciszek Górski Institute of Plant Physiology Polish Academy of Sciences | Poland | about 1 month ago
qualifications Experience in one or more of the following areas will be considered an advantage: RNAseq analysis pipelines, systems biology, modelling biological processes, or machine learning approaches, redox
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, 10 lecturers, 20 postdocs, and 60 doctoral students. Our department has a welcoming culture which nurtures innovativeness and communication among our international and diverse faculty. The department