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related e.g. to the biodiversity crisis, GPS independent navigation, and quantum sensing at ambient temperature. For more information see https://navisense.org/. The Biomimetic robotics research in your PhD
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with a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high
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First Stage Researcher (R1) Positions PhD Positions Application Deadline 17 May 2026 - 23:55 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Is the job funded through
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. Disseminate research through high-impact publications and conference presentations. Requirements: PhD (or near completion) in Imaging Science, Computational Biology, Bioinformatics, Machine Learning, Data
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: · A completed M.Sc. degree in computer science, machine learning, and related fields. · Strong proficiency in English (the working language of the institute). · Capability and willingness
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 6 hours ago
-scale assimilation Develop new interfaces between PDAF and different data assimilation systems of project partners and to machine-learning based assimilation methods Extend the ensemble assimilation
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Toxicology (https://www.dife.de/en/research/departments-and-labs/molecular-toxicology/ ). What we offer This PhD position is funded by the Marie Skłodowska-Curie Actions (MSCA) of the European Union's Europe
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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assessment, programming and machine learning. If so, we encourage you to apply! You will develop exposure and physical vulnerability maps for past and future (1970-2100) and integrate these into a flood risk