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interface of machine learning, deep learning, data science and applications in forest sciences. Together with the Director, you will further develop KIForst as a faculty-wide platform for methodological
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position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Job description:Staff Scientist / PostDoc – Machine Learning for Scientific Applications You
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for a Professorship (W2) (5 years/tenure track) of Statistical and Machine Learning in the Life Sciences, combined with the lead of a research group Computational Statistics & Dynamical Systems for Life
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are seeking a PhD candidate to join our young team (Computational Systems Medicine) within the context of the BMFTR-funded DIASyM (https://diasym.mscoresys.de/ ) project, to develop new statistical and
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 24 hours ago
. or Diploma in bioinformatics or a comparable qualification Extensive programming experience Practical experience in machine learning and the application of large language models Knowledge of OMICS and image
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for Philosophy of Machine Learning for Science (m/w/d) to commence as soon as possible. The tenure-track position is embedded in the Cluster of Excellence “Machine Learning: New Perspectives for Science
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implementation and commissioning Knowledge of machine learning or reinforcement learning applied to control systems is a strong asset Experience with accelerator technology, specifically photocathodes is an asset
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=29009 Data Scientist/Computational Scientist – Multimodal and Multi-Agent AI for Precision Oncology (m
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19.08.2026 Application deadline : 15.11.2026 The Tübingen AI Center invites applications for two tenured full professorships (W3) in Machine Learning and Intelligent Systems (m/w/d), to start as
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, including gas turbines and combustion engines. We combine advanced computational fluid dynamics, theory, machine learning, high-performance computing, and experimental methods to investigate and model complex