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The Vrije Universiteit Amsterdam School of Business and Economics is seeking an all-round data scientist for 1 FTE for a period up to March 2025 in the project FIRMBACKBONE (FBB). The project team of researchers consists of Prof. dr. Wolter Hassink (UU/USE), Prof. dr. Arjen van Witteloostuijn...
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the access to modern High-Performance Computing (HPC) systems in the context of finite-element based scientific simulations. You will research new source-to-source compilation technology able to translate
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between public values and AI and digital technology. Research in the lab broadly examines the implications of the growing reliance on AI and digital technologies for public administration and governance
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. Requirements A MSc degree in Human Movement Sciences or related field such as Biomedical Technology, Human Computer Interaction. Comfortable with programming in Matlab, Python, and/or Unity. Experience with
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Artificial Intelligence, Cognitive Science, or related interdisciplinary fields such as Interaction Technology that combines an understanding of the underlying AI technology and human-centered approaches
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the end of the 4-year project. Requirements a Master's degree or equivalent in (applied) physics, engineering, or a related field, ideally with a background in optics and imaging proficiency in numerics
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of decoloniality and indigeneity; climate change, natural resources, and environment; digital society and technology; and anthropologists working on conflicts, borders, and identities. You will have considerable
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, you must hold a university masters’ degree in science and technology studies (STS), communication sciences, or a related field, such as political sciences, anthropology, sociology, etc. You must have
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to the enormous advancement of computer technology. Nevertheless, the models used to study these chemical processes are, up to now, underdeveloped, hampering the ability to obtain the causality behind the observed
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engineering, earth or environmental science with a hydrogeology / groundwater focus experience with (groundwater) data analysis experience with modelling; ideally socio-hydrological modelling (e.g. system