53 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" positions at Leiden University
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the interests of its scientists. As such, there are plenty of opportunities to learn new skills, expand your knowledge, collaborate across disciplines, and experiment in a friendly environment fully embodying
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://www.universiteitleiden.nl/en/science/mathematics . What you bring The successful candidate is expected to have: A master in statistics, (applied) mathematics, machine learning or a closely-related quantitive discipline (to
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are located at the heart of Leiden’s Bio Science Park, one of Europe’s biggest science parks, where university and business life come together. For more information, see http://www.science.leidenuniv.nl
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eligible for a substantial tax break. For more information about employment conditions, see https://www.universiteitleiden.nl/en/working-at/job-application-procedure-and-employment-conditions What we find
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: https://www.universiteitleiden.nl/en/archaeology . What you bring In this team, we are looking for someone who can work independently but collaboratively. Every job is different, so in the beginning we
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national and international events and conferences; proficient in general computer skills and experience with electronic collaboration tools; and willing to learn the Dutch language. The working language of
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are committed to academic innovation and fostering a close-knit, inclusive community where everyone feels welcome and valued. For more information about Leiden Observatory, see here: https
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possibility for negotiation). In this post you are expected to: teach (in English) the course “Stochastische Besliskunde” (“Stochastic Operations Research”), consisting of one two-hour lecture per week together
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organismal domains and data modalities, making use of state-of-the-art methodologies such as systems/network analysis, artificial intelligence and machine learning and/or computational modelling approaches
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enhance real-time decision-making in road traffic management. The project aims to bridge the gap between recent advances in AI and machine learning, in particular, multimodal and instruction-tuned