93 machine-learning-"https:" "https:" "https:" "https:" "https:" PhD positions in Germany
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), the sorption of PFAS and heavy metals onto natural nanoparticles will be investigated in situ using a dedicated field exposure method developed by our team, complemented by laboratory experiments and machine
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key
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Degree Dr rer nat Course location Münster Teaching language English Languages English only Programme duration 6 semesters Beginning Only for doctoral programmes: any time Application deadline https
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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Job related to staff position within a Research Infrastructure? No Offer Description PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1
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of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both
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, statistics, machine learning) - a high motivation and the ability to work independently with a strong team orientation - excellent spoken and written English and the will to acquire a certain working language
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-good university degree in economics - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) - a high motivation and the
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data Your Profile The ideal applicant has a strong background in bioinformatics and/or probabilistic machine learning, as well as experience in omics data analysis, and possesses solid English-language