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compilation, optimization and error mitigation collaborate with theoretical computer scientists on developing noise-aware quantum programming paradigms Your Profile: Master in physics, computer science
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reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable the smooth processing of big data in the context of scientific, AI
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Reference Number: 11180 Fixed-term of 3 years | Part-time with 65% (25 hours/week) | Salary according to TV-L EG13 | European Institute for Molecular Imaging We are UKM. We have a clear social mission and, with our focus on healthcare, research, and teaching, we bear a unique responsibility. To...
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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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(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