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use of solar energy. https://www.epfl.ch/labs/sci-enac-as/ Main duties and responsibilities As a PhD Student, you will be expected to: Assume full responsibility for your PhD dissertation; Perform
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are most important for the use of solar energy. https://www.epfl.ch/labs/sci-enac-as/ Main duties and responsibilities As a PhD Student, you will be expected to: Assume full responsibility for your
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<span lang="en">TUD Dresden University of Technology</span> | Dresden, Sachsen | Germany | about 14 hours ago
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At the Faculty of Electrical and Computer Engineering, Institute of Circuits and Systems, the Chair of Highly-Parallel VLSI Systems and Neuro
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Australian National University | Canberra, Australian Capital Territory | Australia | about 9 hours ago
proficiency in data, sensors, and operational strategies. In parallel, MDBA, the principal governmental water agency, assumes responsibility for integrated and sustainable basin management. Their
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, ranks among the top 20 universities worldwide and offers an exceptional working environment with very competitive salaries. The IMOS Lab (https://www.epfl.ch/labs/imos/ ) offers a highly motivating
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arc energy distribution becomes particularly complex in scenarios like parallel-pass deposition, thin-wall deposition, and off-centre or out-of-position deposition. Additionally, FEA models are focused
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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
modelling from Project 1, we will conduct focus groups and interviews with communities in high- and low-risk zones to capture local knowledge, behaviours, and risk perceptions related to AMR. In parallel
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German Cancer Research Center in the Helmholtz Association (DKFZ) | Oettingen in Bayern, Bayern | Germany | 13 days ago
and Functional Genomics ( https://www.translatum.tum.de/translatum/forschungsgruppen/rad-roland-experimentelle-krebsgenetik/ ) at the DKTK partner site Munich, starting at the earliest date possible
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and Product Development, where multiple externally funded research projects are conducted in parallel in close collaboration with industry, public authorities, and international partners.The successful
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for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing