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, compression, learning, and inference for classical and quantum data exchanged through classical and quantum networks. The objective of the PhD study is to explore and address research and design challenges
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functional priors from billions of years of evolution; how to compress measurements with controlled mixtures of molecules; and how to align models of laboratory experiments with observational human biology
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. The position will involve development of codes/models simulating the nucleation and propagation of stress corrosion cracking in samples under low cycle fatigue conditions, as well as models for linking
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include developing efficient code in Python and Julia to perform numerical optimization of control fields that govern the evolution of the photonic quantum information processor. This includes adaptation
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doubts about the quality of the code produced. If you want to investigate the effect that adoption of GenAI has on software development, as well as building tools for mitigating the risks, verifying
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code, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and
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designs, building effective and conceptual models to inform our theoretical understanding, and developing code and theory frameworks to address new topological phenomena. Depending on the project’s results
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. The position will involve development of codes/models simulating the nucleation and propagation of stress corrosion cracking in samples under low cycle fatigue conditions, as well as models for linking
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international PhD researchers, gaining access to dedicated training events, coding bootcamps, hackathons, and transferable skills workshops as part of the MSCA Doctoral Network programme. Based at DTU Wind’s
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engineering, mathematical and programming contexts Your research will include extending and contributing to models and codes, including both high- and low-level programming languages, e.g. Python/Matlab