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Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 23 hours ago
, virtual reality, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling humans and animals shape and behavior. In the Eye
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for the ERC Advanced Grant project “Equilibrium Learning, Uncertainty, and Dynamics.” **Positions Available** We invite applications for Doctoral Researchers with a strong background in machine learning and an
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How to apply:uom.link/pgr-apply-2425 [uom.link] This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free stipend set at the UKRI rate
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years of post-qualification experience at the time of application; (b) experience in using machine learning for research projects; and (c) have a good command of both written and spoken English
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environment with excellent infrastructure. The candidate will benefit from joint supervision by Prof. Olga Fink (EPFL IMOS) and the UESL team at Empa, combining cutting-edge expertise in machine learning and
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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We are seeking a highly talented and experienced Postdoctoral Researcher to join a research team led by Prof Chris Summerfield focussed on studying learning and decision-making in humans and machine
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involve directed evolution and protein optimisation, applying molecular biology and biophysics. Researchers will be supported to develop skills in the latest AI or machine learning tools for protein design
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completed, or be close to completing, a PhD/DPhil in a relevant quantitative field together with a demonstrable track record in studying humans and machine learning models. Advanced programming and
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machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab