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PhD studentship: Discovery of rational therapeutic biomarkers in breast cancer by systems pathology and deep learning Supervisor: Dr Hamid Raza Ali Department/location:Cancer Research UK Cambridge
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25th September 2026 Languages English English English The Department of Marine Technology has a vacancy for a PhD Candidate in Deep Learning Enhanced FSI analysis of Modular Floating Structures PhD
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
University. Project description This fellowship forms part of the Novo Nordisk Foundation-funded project “Deep Learning-Accelerated Crystallography Pipeline”, a collaboration between Durham University
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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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robot learning and edge deployment. Closing date: 15 August Overview Robotics is entering a new phase where foundation models connect perception, language and action. Vision-language-action models, robot
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predicts something important? This project will uncover the neural circuits that transform visual information into dopamine signals that teach the brain about motivation, action and decision-making
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Learning Matters!. Task You will break with the current focus on the brain to uncover the physics of continual learning instead by investigating the emergence of learning bottom-up in life, reduced in
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–2 years, total 3–4 years) on deep learning for medical imaging. This DFG-funded project focuses on developing deep learning methods for medical and scientific imaging. The Professorship for Machine
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selection and validation, supervised and unsupervised learning, optimization techniques, (deep) neural networks, probabilistic methods and statistics, data visualization, natural language processing
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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep