531 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof"-"Prof" positions in Denmark
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more sustainable? If you share our passion for technology and the difference it can make in meeting the UN’s Sustainable Development Goals, perhaps you are one of our two new PhD students. At DTU Electro
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, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured light-trapping
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optimization, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured
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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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Position Location: Odense, 5230, Denmark [map ] Subject Areas: Pure math with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. Appl Deadline: 2025
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-tasks and language models. This position is part of SDU’s initiative to develop energy-efficient AI accelerators based on alternative model architectures that cannot be leveraged as efficiently
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of the following areas: Research and development within computer vision and machine learning. Research and development within UAS platforms, subsystems, and payloads. Software design and development (C, C++, Python
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to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies. This is an exciting
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to material, cutting tools and parts production. The PhD project will therefore focus on the development of an integrated system combining direct and indirect tool wear monitoring for reliable residual life
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing