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The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we are seeking a highly talented and motivated PhD student within the field
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perform prioritized Non-Targeted Assessment across diverse water matrices and case studies, while the AI4Science PhD will develop machine‑learning models that learn from and build upon these pNTA results
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and machine learning. Internal further training & coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your skills in over 600 courses
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research environment for biophysics. Our group combines molecular dynamics simulations with machine learning techniques to understand how proteins, biomembranes, and small drug-like molecules interact
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contribution of the PhD will be the derivation of multilayered approaches for motion planning and control based on the XS-Graphs, where both model-based and learning-based solutions are foreseen. This includes
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mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. Modeling Atomic Processes on Nanoparticles Develop atomistic models and machine-learning
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, or a closely related field Strong programming skills, e.g., Python, and familiarity with machine learning and/or software engineering workflows; experience with Git and empirical evaluation Experience
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the Arctic, experimental tests of climate driven changes in carbon export from land and turnover and release of greenhouse gases (CO2 and CH4 ) from headwaters, and use of machine learning and process-based
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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if they demonstrate strong relevant skills. Coursework or strong background in computational mechanics / FEM, numerical methods, and scientific programming. Exposure to machine learning / data-driven modelling and/or