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Vacancies PostDoc position on VR training for first responders dealing with “Personen met Onbegrepen Gedrag” (Dutch language) Key takeaways We offer a challenging PostDoc position with the Human
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 24 days ago
of meteorites as well as numerical modeling on state-of-the-art supercomputers. We invite applications for a Postdoctoral Position (m/f/d) in machine learning for PDEs and turbulence control. Machine learning
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Do you want to be part of a young, dynamic research group working on designing the next generation of sustainable energy materials using computational chemistry and machine learning? And do you see
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willingness to become familiar with the other, as well as multi-agent systems and ontologies. 4. Excellent Python programming skills, and familiarity with standard machine learning libraries. 5
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mathematical, statistical, and machine-learning-based analysis of complex data sets, such as hypothesis testing, supervised/unsupervised learning, linear models, etc. Experience with atlas-scale single-cell data
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and implement novel computational strategies that combine physics-based modeling, optimization techniques, and machine learning approaches to improve cryo-ET image processing workflows. This includes
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experience with distributed control, cyber-physical systems, smart transformers, machine learning, power systems or systems engineering. You have solid skills in modelling and simulation using software tools
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. You'll be part of the Tactile Machines Lab, which is a dynamic, interdisciplinary group of researcher bringing together expertise in robotics, sensing, machine learning, biomechanics, and haptics
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the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
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computational imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely