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partners. The main goal of your PhD project will be to develop combined X-ray and visible-light imaging technologies and machine learning methods for high-throughput inspection tasks. The work will include
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even makes room for good conversations over high-quality tea. Job description As a PhD candidate, you will contribute to cutting-edge research on next-generation wireless communication and sensing
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problems, numerical mathematics, optimisation, machine learning and imaging physics, with applications ranging from medical and industrial imaging to geophysics. For more information, please visit
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discipline. Prior experience in any of the following is a plus but not essential: ultrasound or wave physics, numerical simulation, Python programming, and machine learning frameworks. Most importantly, we
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IOCB Prague (Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences) | Czech | 2 months ago
bioinformatics or molecular biology position. We're looking for someone genuinely excited by the intersection of structural/molecular biology, physics-based simulation, and machine learning/deep learning – a
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, statistical methods, or machine learning is considered a merit. Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University´s rules and guidelines
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how machine-learning-based methods can help overcome this bottleneck, opening the door to excited-state simulations at scales and system sizes that are currently out of reach. You will work at the
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, and machine learning methods, choosing the approach that best fits the scientific question. Investigate systematically what information is contained in imaging data, how it can be extracted, and how
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, Physics, Electrical Engineering, Communication Engineering, or equivalents; – Knowledge in artificial intelligence, statistical and machine learning, complex systems, agent-based modeling and simulation
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices