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, machine-learning methods and predictive calculations of defects and transport properties. The position will also be integrated into the wider CENSEMAT research environment at Aarhus University, allowing
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Independent Junior Research Group Leader (m/f/d, E14 TV-L, 100%) on Machine Learning Methods for Des
, 100%) on Machine Learning Methods for Des Employer University of Stuttgart Location Stuttgart, Baden-Württemberg (DE) Salary German public-sector collective agreement (TV-L, Tarifvertrag für den
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structured, well-documented way that supports benchmarking, reproducibility, and reuse by others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent
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mineral resources Expertise in predictive or machine learning-based spatial modeling in a geoscience context Experience with the operation of deep marine research instruments at sea Application
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applications for a Postdoctoral Fellow with Professor Pragya Sur. Professor Sur’s lab focuses on research in high-dimensional statistics, machine learning theory, or more broadly, mathematical foundations of
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multidisciplinary areas of bio-based composites, fibre reinforced thermoplastics, acoustic engineering, machine learning, and injection moulding process optimisation together with world leading research
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of up to 2 years. The place of employment will be in Odense. Research profiles and tasks We are looking for a candidate with a background in computational social sciences, machine learning or data
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machine learning–based analysis. Behavioral features are compared at inter- and intra-disease levels to identify disease-specific signatures and establish a foundation for future circuit-level
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Job Description If you are looking to establish yourself as a researcher in the cross-disciplinary fields of machine learning and mental health, this postdoc position is for you. At DTU Compute you
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Familiarity with machine learning or advanced data-driven approaches for biological data analysis Demonstrated ability to work in interdisciplinary and collaborative research environments, with strong