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Postdoc (f/m/d) Leader of Junior Research Group "WEEE-Recycling" / Completed university studies (...
-hand experience in the application of machine learning, simulation and modelling concepts in resource technology # Proven track record of interdisciplinary collaboration along the value chain of raw
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in Canada, USA, Sweden and the Netherlands. At the University of Hamburg the PostDoc will work in a team consisting of senior scientists, PostDocs, as well as a PhD student and technician hired through
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and others) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics
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. Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 2 months ago
the University Medical Center Groningen (UMCG) in the Netherlands. This position is based in the Translational Psychology Group, a Heisenberg Professorship funded by the German Research Foundation (DFG) and led by
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to cover a wider variety of physics use cases. Developing methods to make machine-learning-based models portable and interoperable. Leading the definition of containerized and networked “Models as a Service
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-party research funding are expected. We are particularly interested in a candidate in any field of economics who leverages state-of-the-art machine learning and causal inference methods to innovative
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Documented expertise in developing and training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium and the Cluster of Excellence "Machine Learning: New Perspectives for Science". Details