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Field
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candidates will have: A solid grounding in mathematical or physical sciences Interest in dynamical systems and complex system behaviour Some coding experience (Python and/or Julia) Enthusiasm for working
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for this application process Additional comments Wageningen University & Research is the university and research centre for life sciences. The themes we deal with are relevant to everyone around the world and Wageningen
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
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, or defect evolution modify electrical transport properties. While magnetic permeability effects will not be excluded where relevant, the central aim is to establish a robust, physically grounded conductivity
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Application deadline: 30.09.26 Research theme: Applied Mathematics, Thermal-Fluid-Dynamics, Multi-Physics How to apply: https://uom.link/pgr-apply-2425 UK only This 4 year PhD project is fully
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10 Jul 2026 Job Information Organisation/Company VUB Department Department of Applied Physics and Photonics Research Field Engineering » Precision engineering Researcher Profile First Stage
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
optimizing complex systems across a wide range of domains, from industrial manufacturing and energy to environmental monitoring and healthcare. The Engineering Digital Twin EDT program , funded by the France
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in complex biological networks e.g. food webs, forming the foundation of natural ecosystems. Yet, we lack the tools to predict how these networks change in time and space. This is especially critical
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collection and analysis is considered an advantage. Experience with case study research, interviews, observations, document analysis, or process-oriented research designs will be particularly relevant. We
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, physics of fluids, flow control... The main objective is to develop numerical tools to efficiently predict and to deeply understand flows in more and more physically and geometrically complex configurations