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passionate about sustainability, clean energy, and water treatment technologies?Are you skilled in machine learning, process modelling, or chemical engineering simulations?Are you excited by the idea
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allowed computational fluid dynamics (CFD) to flourish, becoming an indispensable for many industries. Simulating the full Navier-Stokes equations is computationally prohibitive for most applications, so
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 2 days ago
the reference COMPETE2030-FEDER-00683900, Operation No. 15733, funded by COMPETE2030 and national funds (FCT) under Call for Applications no. MPr-2023-12. Scientific Area: Neuroscience and Neuroengineering 1
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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We’re seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon
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the feasibility of novel ultralow-power electronics based on quantum-mechanical tunnelling processes in advanced CMOS, which has a strong potential for Internet-of-Things devices and edge-artificial intelligence
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generation unit, imaging lenses, scanning system, and signal detection within a multi-beam framework. For this purpose, you will use commercial simulation software tools such as EOD and GPT, while also
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to increase synergy and impact to the region and nation. The positions will concentrate on computational simulations and AI-driven tools, including materials discovery, design, property prediction, process