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major themes—cardiovascular science, neuroscience and immunology—addressing key organ systems targeted by non-communicable diseases. About the role The IDRM Transition Fellowship programme aims to support
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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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research in social, affective, and health neuroscience. English is the working language of the team, but speaking French or an interest in learning French will be advantageous. Where to apply Website https
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Because of the drastically increasing demand from AI/ML applications, the computing hardware industry has gravitated towards data formats narrower than the IEEE double format that most computational
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We invite applications from researchers to join our XR (extended reality) and Visual Computing research groups. We have 3 posts available from 1 May but there is flexibility for later start dates
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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significant impact on the world around us. Carnegie Mellon University’s department of Electrical and Computer Engineering is searching for a Postdoctoral Research Associate to work on an interdisciplinary
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work on public health interventions to reduce consumption of harmful ultraprocessed foods (UPFs). Based in the Population Health Interventions Programme, the primary role of this post is to lead
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Postdoctoral Research Associate - Hybrid Computational-Experimental Scientist in Bacterial Drug Resp
Job Description We are seeking an interdisciplinary postdoctoral researcher to join our lab at St. Jude Children's Research Hospital to develop new experimental-computational approaches for studying