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neuroscience or a related field. Experience of MEG/OPM-MEG acquisition and data analysis is essential. Experience with MATLAB or Python computer programming for neuroimaging data analysis is essential
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on Experimental Study and Computational Solids Mechanics model of soft multifunctional materials such as magneto-active polymers (MAPs), Electro-active polymers (EAPs). The successful candidate will work on the
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the starting date is negotiable. The current funding is guaranteed from the Montague Burton Fund. We are looking for a candidate who is a health economist with excellent computational skills. The post is
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the Department of Engineering Science at the University of Oxford. The post is funded by the Oxford Martin Programme on Circular Battery Economies. It is fixed term up to December 2027. You will undertake
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emphasis on research infrastructure and technology rather than preparation for an academic career path. You will be involved in research, but more focused on learning and improving how computing, workflows
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. Familiarity with neurophysiological research methods (e.g. EEG and/or EMG), including participant setup, data acquisition, and preliminary signal quality checks. Experience with data management and research
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C and python, familiarity with
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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essential. Experience with MATLAB or Python computer programming for neuroimaging data analysis is essential. Experience in MRI and/or EEG acquisition and analysis is desirable. Experience working on research
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, experience managing and analysing ancestrally diverse genomic datasets, and expertise in computational genetics, including variant annotation and genome-scale analyses. Proficiency in R or Python, excellent