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Field
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at the interface of modelling, system design, and control engineering, contributing to the development of the next generation of intelligent, energy-efficient hydraulic systems. The position is offered in
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mechanisms, and distinguish cells that prevent productive infection from those that become infected but survive or delay killing. The post is based in Central Cambridge, UK. The successful applicant will
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, verification and control of LLM-based agents AI for materials discovery – generative models, active learning and autonomous discovery of novel materials We welcome applications from candidates whose interests
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on information theory, machine learning, and control to analyse how local variability, sensor drift, and platform differences affect both global model performance and human supervisory factors such as workload and
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, modelling and observing, and Arctic pathways for policy-relevant solutions. This position contributes to the modelling and observing theme, developing radar-based methods for ice drift and situational
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and fostering a positive and productive team environment A good command of both written and spoken English. We consider it a plus if you have previous experience in sequencing-based DNA methylation and
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PROJECT DESCRIPTION Research aims at developing a wind-farm control emulator by coupling large-eddy simulations and aeroelastic turbine models with meso-scale weather models to run realistic wind-farm
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
-supervised by: Mohamed Maouche, Researcher at Inria Raouf Kerkouche, Researcher at Inria Sonia Ben Mokhtar, Researcher at CNRS Scientific context Recent advances in Large Language Models (LLMs) have enabled
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23rd September 2026 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Efficient Edge Intelligence Models Apply for this job See advertisement
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cultivated in northern and remote locations. ACRD’s research interests include integrating engineering, intelligent systems, data analytics, and plant biotechnology to optimize crop production in controlled