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which technology and research fields are advancing. Furthermore, you will also extend the indicator beyond novelty toward quality assessment and validate the reliability, robustness, and fairness of LLM
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finding robust ways to extract biological information even when datasets are small, heterogeneous or noisy. We value scientific curiosity and persistence over blind application of standard pipelines
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conditions and develop robust solutions for time- and energy-critical applications. Design embedded hardware: Develop experimental measurement setups, integrate sensors into embedded platforms and work with
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
to understand the imaging pipeline, and finding robust ways to extract biological information even when datasets are small, heterogeneous or noisy. We value scientific curiosity and persistence over blind
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PhD student (f/m/d) who wants to take ownership of the software ecosystem behind our computational imaging research – from experimental reconstruction algorithms used inside our lab to robust tools used
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production and characterisation of inks, interfaces and functional layers Establishment of robust characterisation workflows to link ink formulation, layer structure and electrochemical parameters Benchmarking
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, you will also extend the indicator beyond novelty toward quality assessment and validate the reliability, robustness, and fairness of LLM-based research indicators. The main use case for assessing
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discovery and inference, with an emphasis on robustness, scalability, uncertainty quantification, expert knowledge integration, and multi-scale causal abstraction and representation learning. Your Job How are
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
of sea ice conditions, there is the opportunity to develop more robust and higher-resolution data products useful for Arctic communities. This PhD project falls within an international effort to co-develop
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, computability, and robustness of methods from Deep Learning. Your tasks • Contribution to the research project “Stability and Solvability in Deep Learning”, where your research will be a part of your dissertation