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. The thesis project will focus on radiation-induced processes at oxide–water interfaces, investigated using advanced experimental and theoretical methods. The position is for four years of doctoral
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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The Einstein Telescope is a next-generation research infrastructure currently in development, featuring a large-scale computing center whose energy demands present a unique opportunity: to develop climate-neutral operations through the integration of renewable energy sources and hybrid storage...
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-performance computing and parallel algorithms. Selection process Applicants should submit a CV, academic transcripts and a motivation letter through the KU Leuven application portal. In addition, candidates
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algebra of assembly (sequential, parallel, feedback, refinement); semantic projections and system-level invariants over trajectories. Architecture synthesis as an inverse problem — given a specification
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pumping technologies for future electrified energy systems. We are currently recruiting a PhD candidate at DTU for a project on the multi-physics modelling of bearingless pumps. A parallel PhD position is
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position Long term management of large scale computing infrastructures requires
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. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. ... (Video unable to load
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 2 months ago
of biomolecules. All models will be experimentally validated using data generated in parallel projects, either relying on droplet microfluidics (for thermodynamics and kinetics) or on large-scale setups (process
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scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing predictive performance, generalisation