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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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of computational approaches to large scale simulations Basic knowledge of (geo)chemical processes and machine learning will be of advantage Expertise in Machine Learning approaches, ideally beyond neural networks
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suitable for part-time employment. Starting date: 12.02.2025 Job description: We are seeking a PhD student to investigate data-driven biodiversity classification in a stakeholder process, particularly how
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development of artificial intelligence (AI) software for topology-informed biomedical image analysis and large foundation models. You will be responsible for Develop new machine learning algorithms
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RPTU University of Kaiserslautern-Landau • | Kaiserslautern, Rheinland Pfalz | Germany | about 18 hours ago
communication tailored to their needs. For further information, see: https://www.physik.uni-kl.de/oscar/ Course organisation During the research work, the PhD student has the possibility to participate in
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The molecular biosciences are undergoing a major paradigm shift – away from analysing individual genes and proteins to studying large molecular machines and cellular pathways, with the ultimate goal
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-based products, is among the areas that more quickly is adopting AI. Machine learning (ML) algorithms are being developed and integrated in microscopes for its autonomous operation and in software
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data engineering. The research will focus on data preparation and data pipelines for complex machine learning (ML) systems. Such ML systems are increasingly used to automate impactful decisions but
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
Your Profile PhD in Geophysics, Electrical Engineering, Physics, Oceanography, Climate Sciences or related fields Strong background in machine learning and remote sensing Experience working with large
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are predominately held in English. Full-time / part-time part-time (study alongside work) full-time Programme duration 8 semesters Beginning Only for doctoral programmes: any time Additional information on beginning