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11.12.2025 Application deadline: 15.02.2026 The Faculty of Science at Tübingen University invites applications for a W3-Professorship in Machine Learning in Physics at the Department of Physics (m/f
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related to learning engineering and AI in education, working with a team of postdoctoral researchers, PhD students, and Master’s/undergraduate researchers across multiple universities and organizations
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a current curriculum vitae, research statement, and a cover letter. Contact information for three references is required. To learn more about AI at Princeton, please visit https://ai.princeton.edu
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allow users to input CDR forcing (e.g., alkalinity addition) and produce day-by-day forecasts of CO2 uptake and storage durability. The project combines physics-based modeling, machine learning, and high
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resources for the broader education research and developer community. The Postdoctoral Associate will participate in cross-disciplinary research and development projects related to learning engineering and AI
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential
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, statistical and machine learning, involving analysis of biological multi-modal and multivariate data, or related fields, is a requirement. Experience with computational modeling in metabolomics and metabolic
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and validate their methods using real-world systems. Postdoctoral fellows will work across the following research areas: Predictive machine learning Robust and stochastic optimization Learning-enabled
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manufacturing principles. Experience with machine learning methods and integration into hybrid modelling systems Demonstrated ability to clearly communicate research concepts and results in high-quality journal
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Employer https://main.hercjobs.org/jobs/21909436/postdoctoral-research-associate Return to Search Results