35 natural-language-processing-phd Postdoctoral positions at University of London in Uk
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interest to identify cancer drivers from genomic data using machine learning (Mourikis Nature Comms 2019, Nulsen Genome Medicine 2021), study their interplay the immune microenvironment (Misetic Genome
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develop, synthesise and characterise materials for this project. About You The post is suited to a PhD graduate with a background in materials chemistry or a related discipline. If you have a vivid
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help supervise BSc, MSci, and PhD students. The successful applicant will have a PhD in Astrophysics, Theoretical Physics, or a related discipline and prior experience relevant to the post. It is also
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of pediatric brain tumours (Vinel et al BMC Biology 2025, Constantinou et al Cell Reports 2024 and Vinel et al. Nature Communications 2021) to develop new personalised therapies. About You We seek an ambitious
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under real-world conditions. The role includes collaboration with leading 2D materials manufacturers, offering potential for interdisciplinary research and travel. About You You should have a PhD (or be
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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence
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at each stage of the recruitment process for any candidate with a disability. We are open to considering applications from candidates wishing to work flexibly. *PhD candidates who are close to completion
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collaborate with bioinformaticians, experimentalists and clinicians. About You Essential requirements for this post include a PhD in a relevant biological or computational subject and background in
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partners at NHS England and Nuffield Health. About You You will have a PHD (or close to completion) or experience at a comparable level in a relevant subject area. You will have experience of working with
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physiologically relevant models will provide crucial platforms to mimic disease pathology, and better understand and treat tendinopathy. The project will generate tendon-chips using in-house commercially available