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pressure and temperature levels; - Validate the numerical model of the complete system by comparison with experimental data; - Identify improvement strategies for performance and system robustness. Work
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around us? At Maastricht University, you will investigate how individuals differ in predictive processing by combining behavioural and neural testing with computational modelling. Together with colleagues
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English and meets the university’s English language requirements (https://www.rug.nl/education/phd-programmes/prospective/phd-positions/e… ). - Affinity with and knowledge of basics of AI-modelling and data
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), ecological processes (primary productivity and decomposition rates), and greenhouse gases (3D-printed flux chambers), and investigating how we can use citizen science-driven data streams for model development
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/en/organisation/liu/ida You will be placed at the Human-Centred Systems division in the group of Knowledge Modelling and Cognitive Systems, as part of the Linköping University Semantic Web group
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application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with applications towards materials science. Generative machine learning models have emerged as a
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vivo trials with induced (in rodents) and spontaneous (in dogs and cats) animal models of diabetes – 10% b) Collection and processing of biological samples – 5% c) Conducting in vitro tests
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macroscopic designs for soft-tissue healing. The project will be conducted using in vitro models of bacterial adhesion and fibroblast proliferation in collaboration with University of Gothenburg and in vitro
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at CRAG (from basic science to applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (http
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· developong new genetic algorithms related to finite element (FE) modeling · presentation of results and their disseminatio The successful candidates must be enrolled in PhD School program