394 algorithm-"Multiple"-"U"-"Prof"-"Simons-Foundation" "University of Wisconsin Madison" PhD positions
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of advanced computational techniques. This research will integrate power system modelling, optimisation algorithms, and artificial intelligence (AI) techniques to develop an innovative framework for strategic
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200 people, working in four divisions: Algorithms, AI & Data Science, Software, and Interaction. The atmosphere is collegial and informal. You will join the Human-Centred Computing group
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest ML tools and frameworks
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microscopy and atom probe tomography will be prepared. Finally, you will merge the images by means of deep learning algorithms. Your tasks in detail Development of the experimental protocol for the imaging
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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to muon g-2 from lattice Quantum Chromodynamics and algorithmic developments for multi-level and RG-improved simulations (research group of Urs Wenger) C.) Study of multi-hadron systems, with a focus on
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modeling tools and HDL simulators to validate functionality. Collaborate closely with algorithm designers to co-optimize architecture. Publish results in high-impact journals and conferences. Qualifications
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leverage low-precision accelerators for scientific computing by using a number of tricks, known as "mixed-precision" algorithms. Developing such algorithms is far from trivial. We can look at computational
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quantum processors using this technological platform design and implement optimization techniques for full-stack improvement of quantum algorithms model major sources of experimental error for control