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that prioritise student learning in the age of AI. Job requirements You hold a PhD in Educational Science, Learning Sciences, Social and Behavioural Sciences, Engineering Education, Human-Computer Interaction or a
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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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scientists. You meet the following criteria: • a PhD, or a PhD close to completion, in machine learning, artificial intelligence, computational biology, bioinformatics, computer science or a closely related
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researcher who enjoys developing methods for complex biological data and working closely with experimental scientists. You meet the following criteria: a PhD, or a PhD close to completion, in machine learning
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, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools to the setup Create and validate reproducible automated workflows
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As a postdoctoral researcher, your primary responsibilities will be: Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and
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what you are going to do Design and build flow setups using 3D printer, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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requirements For this postdoctoral role, we are looking for someone with a demonstrated background in SAR processing, SAR applications in agriculture and machine learning: A PhD in Earth Observation, Geodesy
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, with a particular focus on the iron and steel sector. By using TROPOMI observations with advanced machine learning techniques, the project will provide independent information on emission patterns and