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. We highly value collaboration, teaching and outreach. To learn more about our team, we invite you to visit our website: https://klimadynamik.univie.ac.at/ . Ready to be part of our team? Let’s shape
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practices in professional physics and students' engagement in these practices The role of agency in students learning physics practice A mixed-method, longitudinal study on factors related to retention in
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23 Jul 2026 Job Information Organisation/Company University of Twente (UT) Research Field Educational sciences » Education Educational sciences » Learning studies Researcher Profile First Stage
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simulation results with experimental data. This project will integrate advanced AI techniques, including machine learning for parameter optimisation (e.g., Bayesian optimisation, reinforcement learning), AI
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health. Successful candidates may have experience in electron or X-ray microscopy, image analysis, AI and machine learning, quantitative data science or computational modelling. They will be able to work
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highly value collaboration, teaching and outreach. To learn more about our team, we invite you to visit our website: https://klimadynamik.univie.ac.at/ . Ready to be part of our team? Let’s shape
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 3 months ago
Developing computational framework for 3D shape modeling towards biological insights Developing AI-based representation learning framework for data-driven cell modeling Report findings and methods in
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with these groups will create a stimulating work environment with exciting opportunities for personal development and learning about different fields of research. We will consider candidates with various
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-scale resolution. We highly value collaboration, teaching and outreach. To learn more about our team, we invite you to visit our website: https://klimadynamik.univie.ac.at/ . Ready to be part of our team
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models. We further propose to develop scalable structure learning methods for these new models, including latent variable identification, and to demonstrate their effectiveness on real data. For this, we