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Field
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subject by the start date of the appointment Good programming skills (r, Fortran, Python) Familiarity with eco-evolutionary optimality approaches to modelling vegetation Experience with working with large
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About the role We have an exciting opportunity to join the Wood Lab in the Department of Paediatrics as our Postdoctoral Researcher This role is part of a larger interdisciplinary program focused
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, MRtrix, ANTs, or equivalent, and programming or scripting in Python, R, or bash/zsh on Linux/HPC environments. Experience working with clinical research data, including neuroimaging and clinical data
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of Paediatrics as our Postdoctoral Researcher This role is part of a larger interdisciplinary program focused on advancing precision medicines for inherited cardiomyopathies under the CureHeart initiative—a £30
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) Country United Kingdom Application Deadline 24 Sep 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
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, engineering, or a related field. Strong programming skills and experience in machine learning or statistical modelling are essential. Experience with healthcare data, algorithmic fairness, or deep learning
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the universities of Manchester and Oxford. The post-holder will be one of six centre-funded postdoctoral researchers delivering on projects that form our core research programme. They will be a cornerstone of the
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equality. We offer an exciting, stimulating, diverse research environment and actively promote a family friendly workplace. The Institute is also a member of Stonewall’s Diversity Champions programme. The
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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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conceive, plan and independently execute appropriate activities to deadlines. It will be important to communicate effectively, both orally and in writing. Ability to find information, analyse complex data