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Research Associate to join the Northern Net Zero Impact Accelerator project titled ECO-HAVEN: Energy Conservation for Households using Adaptive Edge Learning. This project develops a low-cost, privacy
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accepted. The following experience will strengthen your application: Familiarity with Federated Learning We value a collaborative attitude and an interest in working both in teams and independently. Self
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machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens
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processing approach based on flow patterning to make meter scale LCEs of complex shapes and actuation modes. ALCEMIST builds on a tight synergistic collaboration between the Experimental Soft Matter Physics
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Job Description We invite applications for a fully funded 3-year PhD position in the Embedded Systems Engineering (ESE) research section at DTU Compute in collaboration with the Technical
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, where opportunities for collaboration and learning abound. About the role The role involves undertaking high quality research as part of an exciting new internationally funded research project
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15 full-time researchers offers a stimulating and supportive environment to learn and grow. Your profile Required qualifications: Undergraduate degree in Engineering, Physics or Mathematics with strong
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interest in interdisciplinary research with an eagerness to learn and develop new approaches. Candidates should hold a Masters or equivalent degree in (Bio‑)Chemistry, Biology, or any related field. What we
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great interest in interdisciplinary research with an eagerness to learn and develop new approaches. Candidates should hold a Masters or equivalent degree in (Bio-)Chemistry, Biology, or any related field
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will collaborate with researchers from various disciplines at iHub, Radboud’s interdisciplinary research hub on digitalisation and society. Lastly, you will also collaborate with other researchers from