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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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application! Your work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning
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Join us for an exciting and excellent PhD journey! Everyday user behaviour may affect the environmental performance of household appliances, yet it is often overlooked in environmental assessments
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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are looking for: To qualify as a PhD student, you must have a Master's degree (masterexamen) of 120 credits or a Master’s degree (magisterexamen) of 60 credits in Machine Learning, AI, Data Science, Computer
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university as a workplace Description of work About the
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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education. A) General eligibility requirement You meet the general eligibility requirement for doctoral/third-cycle/PhD education if you: have been awarded a second-cycle/advanced/master qualification (i.e
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: We are looking for a dedicated candidate who is eager to learn new things and contribute valuable knowledge to society’s work on climate adaptation and the conservation of biodiversity. Applicants
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This PhD student position offers a unique opportunity for a dedicated, curious, and independent person. You are interested in biological and chemical processes taking place in wastewater treatment