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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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& CAD, Computational Systems Biology, Graphics and Vision, Information & Data Management, etc. A Ph.D. in Computer Science or an equivalent degree is required. The University of California, Los Angeles is
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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obtaining academic qualifications as well as courses on development of competences at university as a workplace and orientation with regard to further career steps in science, industry and society
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experience with spatial data analysis using GIS tools or spatial libraries and familiarity with common land-use datasets would be advantageous familiarity with environmental or agricultural economics research
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Fieldwork Grant is for fieldwork support to Faculty of Arts Doctor of Philosophy (PhD) graduate researchers, in which the primary data for the PhD thesis can be collected only in a field location (for example
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and materials engineering. For more information about the APE group please use the following link: www.rug.nl/research/ape. The project cooperates with the Bernoulli Institute of Mathematics
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30.06.2025, Wissenschaftliches Personal The Chair of Software Engineering for Business Information Systems (sebis) at the Technical University of Munich is looking for outstanding candidates