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the project, the PhD student will become part of a team at DTU with numerical and experimental expertise in photonic computing. The activities within the project will benefit from synergies with other
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network, including 4 training schools and two workshops. As a participant of the project, the PhD student will become part of a team at DTU with numerical and experimental expertise in photonic computing
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quantitative image analysis, numerical modeling, and explainable AI (XAI) with state-of-the-art biophysical methods. Using techniques such as traction force microscopy, microfluidics, 3D bioprinting, and
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Engineering, Physics, Applied Mathematics, or related discipline. Proven track record in numerical methods and computational fluid dynamics. Proven track record in machine-learning methods for computational
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requirements MSc in Mechanical/Maritime/Aeronautical Engineering, Physics, Applied Mathematics, or related discipline. Proven track record in numerical methods and computational fluid dynamics. Proven track
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This PhD project is at the intersection of electromagnetism, numerical methods, and high-performance parallel computing, with application towards the design and optimisation of integrated circuits
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provide powerful tools to improve the quality and efficiency of data-driven models. In parallel to the development of data-driven models for dynamical systems with geometric structures such as Hamiltonian
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, elaborate illumination profiles, and large computational domains surpassing several thousands cubic wavelengths. Furthermore, you will contribute to adapting the solver for massive parallel processing, as
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, and a solid understanding of numerical analysis and familiarity with the use of analytical tools. They should also have knowledge and experience in parallel coding and spectral methods. They must have
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-Performance Computing for Exascale" contributes to the design and development of numerical methods and software components that will equip future European Exascale and post-Exascale machines. This program is