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benchmarks Debug common post-training issues, including optimisation instability, reward hacking, regressions, and evaluation failures Profile Essential MSc or PhD in Computer Science, Data Science
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, and synthetic materials, actuated by muscle and powered by chemical energy. Perception and Computer Vision: 3D reconstruction, object recognition, and scene understanding that give robots reliable
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Electrical Engineering Mechanical Engineering Physics Neuroscience Computer Science Chemistry or a closely related field Ideal candidates should possess several of the following: Excellent academic
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analysis, and multi-modal integration is a strong asset (e.g, connectivity analysis). A proven track-record in current flow modeling (SIMNIBS) for TMS and/or tDCS. Skilled in programming (Python, MATLAB, R
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interest in developing new approaches at the intersection of fluid dynamics and quantum computing. In particular: You hold a PhD in computational fluid dynamics, applied mathematics, physics, computer
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platform , published in Nature Communications (https://www.nature.com/articles/s41467-020-18059-7), that enables localized, hyper-efficient delivery of therapeutic compounds to specific brain regions
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applications You have good programming skills for image processing, image analysis and/or hardware control. You are eager to learn, can work independently and have a creative and solution-driven mindset
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analysis. Proficiency in statistical programming and data management using software such as SAS, R, or Stata, with strong skills in data manipulation, cleaning, and analysis. Evidence of scholarly
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programming in Python, and comfortable working with version control (git) in a collaborative codebase Fluent, critical use of AI-assisted tools in research and code development, we treat these as part of
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related questions in an interdisciplinary manner (i.e., at the intersection of psychology, technology, and human–computer interaction). We welcome candidates with a strong interest in fundamental