45 parallel-computing-numerical-methods positions at AALTO UNIVERSITY in United Kingdom
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invites applications to Doctoral Researcher positions in Computational Physics The positions are hosted in the Surfaces and Interfaces at the Nanoscale(SIN) group at Aalto, led by Prof. Adam Foster. We
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Computational Design advances generative and immersive design methods by integrating geospatial intelligence to address sustainability challenges in urban and landscape systems. Her research group has
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and Professor of Practice Jouni Punkki. Job description Research activities will involve computational methods relying on physics-based continuum models to assess the mechanical, thermal, and acoustical
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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computational chemistry. Position 2 will seek to develop a new computational method combining atomistic modeling with experimental microscopy as an extension of our group’s original modified Hamiltonian formalism
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—combining rigorous fundamental research with practical, real-world applications. With strong ties to the Finnish water and wastewater industry, the group has successfully led numerous high-impact projects in
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, specialist in computational design and adaptive landscape and territorial systems. The ADAPT Postdoctoral researcher, focusing on AI-driven generative design methods. International partners at ETH Zurich, MIT
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interaction. Programming skills needed to do data analysis (we mainly use Python) You can be interested either in theoretical methods development or applications, or a bit of both Interest in working on a
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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