497 computer-programmer-"https:"-"FEMTO-ST"-"Inserm"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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student to revolutionise electrical machine design and development based on programmable 3D electrical steel technology enabled by advanced manufacturing processes and emerging magnetic materials
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Applications are invited for a PhD studentship in the Department of Computer Science at City, University of London. The successful candidate will work on Agentic Artificial Intelligence—the next
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ultrafast, energy-efficient magnetic switching, a key step toward faster and greener computing. This PhD will pioneer THz spintronics — a new frontier where ultrafast optics meets magnetism. Using femtosecond
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, and edge computing, AASs are evolving into smart, interconnected solutions for addressing the dynamic challenges of modern cities. This project investigates how to coordinate these multifunctional
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to evaluate ideas on complex, realistic configurations and develop a skill set that is highly valued in both academic research and advanced engineering computation. Funding Comment: Covers full tuition, £20,780
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biological materials. The development of novel computer-vision-based techniques for contactless detection, quantification, and prevention of sport injury. The development of robotic humanoid simulator and
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Institute, with close ties to the Department of Computer Science and Technology. Preferred skills/knowledge We are seeking a passionate and collaborative PhD student with a strong background in machine
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: Comparative transcriptomics, orthology inference, positive selection detection, protein domain analysis, phylogenetic comparative methods Computational skills: UNIX/Linux, HPC computing, R, Python You will gain
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programming skills in Python/MATLAB, and an interest in digital twin technologies, cybersecurity and machine learning. Entry Requirements Acceptable first degree: Computer Science or related disciplines
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Project Supervisor - Professor Rudy Lapeer The Birth4Cast “Digital Twin” aims to create a subject-specific computational biomechanics simulator of childbirth from prenatal fetal MRI scans