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. Together we will make technological advances that bring compact, reliable and economical energy management into our homes. Motivation The UK is charging full speed ahead towards its ambitious goal of net
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turnaround times. You will develop and validate new capabilities within XCALibre.jl, Nottingham’s GPU-accelerated, AI-ready CFD framework turning complex coupled physics into practical tools that engineers can
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cryogenic modelling, two-phase CFD, and AI-based reduced-order models to accelerate modelling capability in net‑zero aerospace technologies. Motivation Hydrogen research has accelerated to address the need
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sensors—and analyze the influence of varying environmental conditions on sensor signals and their signal processing. Advance AI-based calibration: You develop approaches to reduce complex and time-consuming
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AI researchers from ANITI, IMT and CERFACS, as well as with researchers/engineers in weather forecastings from the CNRM (Météo-France). Hybridization methods between neural networks and physical models
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. The goal is to enable efficient, robust, and high‑quality situational awareness in complex and dynamic networks, thereby laying the foundation for future autonomous and data‑driven systems. The specific
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Actions(MSCA) Doctoral Network HEPARD PhD Candidate in Health Economics and obesity Apply for this job See advertisement Job description Applications are invited for a 3-year position in a Research
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Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences | Czech | 16 days ago
Chromatin Structural Biology laboratory to investigate how dynamic protein–protein interactions control transcription elongation in chromatin. Transcription by RNA polymerase II relies on a dense network of
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the properties of complex, biological liquids arise from liquid-liquid phase separation. The field of liquid-liquid phase or biomolecular condensates has been a growing field during the last two decades. With
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to plant biosciences where the impact could be huge and as a result exciting opportunities get missed. When we use light to image deep into complex samples there is a common problem that occurs – the light