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Job description - Developing device-to-architecture level models of emerging nanoscale devices (spintronic, resistive, or hybrid) for in-memory and neuromorphic computing. - Exploring hardware-level
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device-to-architecture level models of emerging nanoscale devices (spintronic, resistive, or hybrid) for in-memory and neuromorphic computing. Exploring hardware-level security mechanisms based
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of neural network architectures (as a plus: PINNs, neural operators, transformers/LLM) and NN training. Strong Python programming skills (as a plus: C++ or Julia) and knowledge of scientific computing
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Collaborating across domains, including civil/architectural engineering and energy management This position is deeply interdisciplinary, and will be carried out in close collaboration with The successful
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recent neural network architectures for machine learning (e.g., CNNs, RNNs, GANs); understand AI-perception, SLAM, Robotics and autonomy; communicate effectively in English, orally and in writing; work
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of Concept Grant “Implementation of Super-resolution Ultrasound Real-time microvascular imaging using Erythrocytes” - iSURE. The iSURE project will develop the hardware and software architecture for a novel
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will be in developing new techniques for testing and verifying modern highly concurrent systems, such as weak-memory architectures and highly-distributed databases. The position is also open, to some
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28 Oct 2025 Job Information Organisation/Company UNIVERSITY OF COPENHAGEN Research Field Architecture Arts Educational sciences History Philosophy Religious sciences Language sciences Literature
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experience in system architecture design The following qualifications would be considered strong advantages: Experience with edge AI frameworks (e.g., TensorFlow Lite) Familiarity with mission control systems
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, and deploy large scale generative models for materials discovery. Work and advance the state-of-the-art in diffusion model architectures for materials. Publish scientific papers and present research