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for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling
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In this PhD position, you will help design the next generation of circular plastics systems by combining hands-on polymer processing with data-driven modelling. The PhD study is a full-time, fixed
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the project "Circularity as Opportunity: Engineering Hydrogen-Resistant Circular Steels (CIRHY)", a 6-year research and innovation programme developing next-generation circular steels that can safely operate in
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extra vacation days. Through the UU Terms of Employment Options Model, you can tailor your employment package to your needs. This way, we encourage you to grow in what you do, both in your work and your
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16th October 2026 Languages English English English The Department of Engineering Cybernetics has a vacancy for a PhD Candidate in Hybrid Learning-Control Methods for Autonomous Underwater
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of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current
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engineering, and model building for financial datasets. At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and work together to train models, architect systems, and run
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positions for general criteria for the position. Preferred selection criteria Education or experience combining engineering or transport with data-driven and quantitative methods Experience with railway
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Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of
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Communication sciences Information science Engineering » Communication engineering Engineering » Electronic engineering Mathematics » Applied mathematics Mathematics » Probability theory Mathematics » Algorithms