536 machine-learning-and-image-processing Postdoctoral research jobs in United Kingdom
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deploy models symbiotically with experimental researchers to optimise design and manufacture of Li air electrodes and cells. This will include image-based modelling of electrodes, and finite-element
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to support e-learning, including developing module content, basic website building and coding skills. Diversity Committed to equality and valuing diversity Application Process You will be required to upload a
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Atmospheric Dynamics group in AOPP which looks at the role of dynamical processes globally in weather and climate variability, predictability and change. The role will involve detailed analysis and dynamical
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Full-time: 35 hours per week Fixed-term: 31st March 2026 The School of Informatics at the University of Edinburgh invites applications for 2 Post-doctoral Researcher positions in Quantum Machine
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, intracranial injections of viral vector (to allow optogenetic/chemogenetic manipulation), electrophysiological experiments (single cell neurophysiology) and histology/imaging. You will be based in Dr Sollini’s
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Experience in analysing drugs and metabolites from human breastmilk Competency in using computer software to collect and process data, e.g. use of Excel, statistical software and machine learning approaches
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning, epidemiology
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for the early detection of mild cognitive impairment (MCI) and prediction of its progression to Alzheimer¿s disease through the analysis of corneal nerve images. You will be based in the Institute of Life Course
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developing characterisations of network models and interactions with methods in statistical machine learning. The post holder provides guidance to junior members of the research group including project
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. Familiarity with standard design verification (DV) procedures and continuous integration (CI) setups would be beneficial. Knowledge of machine learning workloads and the design of machine-learning accelerators