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cyanobacteria and Paramecium bursaria. Image data analysis using AI-based tools and programming analysis scripts. Participation in conferences, presentations, and preparation of publications. Intensive exchange
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Description The Munich School for Data Science (MUDS) is a joint initiative of Helmholtz Munich, Helmholtz Institute for RNA-based Infection Research (HIRI), and the German Aerospace Center (DLR
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 3 months ago
complemented by Monte Carlo simulations, triple collocation analysis and data assimilation to develop a frame work for the operational processing and data fusion to finally derive 3- dimensional (dim), and where
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(TUM), Campus Heilbronn. We seek exceptional candidates excited about graph drawing, network visualization, and information visualization. The specific research focus can be chosen by the applicant based
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semantic querying and reasoning over materials-science/physics corpora Developing pipelines for semantic enrichment of unstructured data, including entity recognition, relation extraction, and automatic
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manufacturing", new AI methods for predicting the outcome of AM printing processes under varying bounding conditions are developed. This involves the design of a cyber-physical system incl. a data management
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Your Job: The research will be part of the recent ERC Starting Grant "Atomic Scale Quantum Sensing and Information with Molecular Nanostructures on a Scanning Probe Tip" (ERC-2024-StG, QuSINT). Our
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its maintenance and safety increasingly depend on data. This PhD project will develop new methods that combine remote sensing, physics-based modelling, and Bayesian machine learning to support risk
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13 Nov 2025 Job Information Organisation/Company Universität Siegen Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Country Germany Application Deadline
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are looking for talented people to join us. Your responsibilities include: MI Project IE2501 “Safe Hydrogen Networks: ML-Supported Safety Analysis and Optimized Sensor Placement” Research in the field of safety