44 parallel-computing-numerical-methods positions at AALTO UNIVERSITY in United Kingdom
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transport for inverse problems One of the central topics of the research projects is the further development of theory and methods for the concept of optimal transport for inverse problems. Optimal transport
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, numerical linear algebra, numerical analysis, optimisation, and differential geometry. The project lies at the intersection of numerical linear algebra and Riemannian optimisation, and its main goal is to
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, developing solutions for removing and storing greenhouse gases into the built environment, and developing the life cycle assessment method for quantifying multiple cycles of using building products. Your role
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, including architecture, computational design, computer science, or related fields, who have a proven track record of applying advanced computational methods to real-world environmental challenges. A doctoral
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with numerous doctoral students and post-doctoral researchers. We offer the successful candidate the opportunity to teach and do research in a vibrant and active international community. This position
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advanced quantum optics methods in both discrete and continuous variables with cutting-edge solid-state systems aimed at pushing the limits of fundamental research and applications such as optical computing
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. At the same time, 20-50% of industrial energy is ultimately lost as waste heat. With the rising demand for computing power, data centers are producing increasing amounts of low-grade waste heat. Likewise, as
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develop methods for the recombinant production of post-translationally modified structural proteins, investigate their effects on material assembly and properties, and design new, functional materials. In
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cavity structure enable a mechanism for the controlled Bose-Einstein condensation at room temperature, with applications in all-optical computing Nature Photonics 13 378 (2019) and quantum sensing Nature
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infrastructure, cloud computing, or digital sovereignty Excellent communication and collaboration skills in English Basic understanding of quantitative methods (e.g. multiple regression) Additional selection