11 distributed-algorithm-"Newcastle-University"-"Newcastle-University" PhD scholarships at DAAD
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, their achievements and productivity to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, the newly established Chair of Algorithmic and Structural Graph
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, their achievements and productivity to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, the Chair of Algorithms offers a position as Research Associate
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. About your role: Develop improved physical models of the image formation process in holographic X-ray imaging Design and implement reconstruction algorithms for handling large-scale tomographic data from
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position (contract-based) and one PhD fellowship in Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys). The PhD position is focused on efficient algorithms
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research in a variety of areas in biology and computation, with possible specializations in genomic and molecular biology techniques as well as in algorithms, statistics and artificial intelligence
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for traceability, robustness, and physicochemical correctness Implement and adapt the most promising algorithms to model radionuclide migration in crystalline host rocks Execute proof‑of‑concept ML simulations and
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algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
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Financing yes Type of Position Full PhD Working Language English Required Degree Master Magister (Masters degree course) Areas of study Marketing, Distribution, Commercial Law, Economic Sciences, Economics
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms