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United Kingdom Application Deadline 9 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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interactions. We’re Looking for Someone With: Strong expertise in protein structure prediction, molecular modelling, and docking. Proficiency in LINUX, bash scripting, and high-performance computing environments
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Responsibilities To undertake training to run CONDOR simulations and in biophysics as required. To run and analyse CONDOR simulations on our high-performance computing cluster. To develop a deep-learning model for
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to enable robust robot autonomy in complex, real-world environments. The post sits within our EPSRC Programme Grant in Embodied Intelligence and will advance the state of the art in localisation and scene
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with members of the team and other researchers in the Future of Food programme at the Oxford Martin School. You must hold or be close to the completion of a doctoral degree in a relevant field (e.g. data
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The Role The postholder will contribute to the UKRI-funded Great British Chemicals (GBC) Hub, a seven-year national programme bringing together 10 UK universities, industry partners, and
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researchers in the Future of Food programme at the Oxford Martin School. You must hold or be close to the completion of a doctoral degree in a relevant field (e.g. data science, industrial ecology, geography
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. The successful applicant will investigate the structure, dynamics, and motility of the bacterial Type IV pilus (T4P) machinery in the model organism Thermus thermophilus using theoretical modelling, simulation
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blades. In this role you will: Design, build and optimise optical and inductive thermal NDE rigs for curved, metre‑scale blade sections; Develop and validate forward–inverse heat‑transfer models