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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics
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settle into the team and are given structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide: https://go.fzj.de
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Hochschule Bielefeld – University of Applied Sciences and Arts | Bielefeld, Nordrhein Westfalen | Germany | 5 days ago
, health campaigns or vaccination programmes. — Work at a university that is open to the world and strongly oriented towards sustainability, diversity and internationality. Would you like to learn more? Find
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outstanding infrastructure ENVIRONMENT: A creative work environment at a leading research facility, located on an attractive research campus at the TZA Aachen https://tza-aachen.de and the Forschungszentrum
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
) appointments FLEXIBILITY: Flexible working time models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to tailor your working hours to suit your individual needs HEALTH
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workshops, soft skills training and social events. Doctoral candidates in the BGTS study programme can pursue their doctoral studies within the programme of a participating research training group (https
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, please see https://www.uni-jena.de/en/Jena+living+international . Funding opportunities within the university Yes Description of the above-mentioned funding opportunities within the university
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data. Develop and apply machine learning models to estimate uncertainty in climate impact statements. Analyse spatial and temporal patterns and trends in climate-extreme impacts. Cross-validate
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research
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estimation, causal discovery, and concept-based explanation techniques Integration of causal and XAI methods into machine learning pipelines within the CRC 1294 “Data Assimilation” Implementation, evaluation