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The Franciszek Górski Institute of Plant Physiology Polish Academy of Sciences | Poland | 25 days 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
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. The focus of this position is developing methods to disentangle dynamic, multiscale ecological signals from large, noisy observational data. This work lies at the interface of statistics, machine learning/AI
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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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). 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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want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
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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
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; Generation of reports and scientific publications; Engagement with students and postdocs and provision of technical support within the UNR Wildfire Hub and beyond; Making presentations in scientific
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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