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. Basic proficiency in programming or scripting (e.g., Python, MATLAB, or similar) for data processing or device control. 4. Ability to set up, calibrate, and troubleshoot sensor systems (e.g., IMUs
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, and manage complex longitudinal datasets using reproducible analytical workflows, with high-level proficiency in statistical programming (e.g., R or Python). Evidence of a developing publication record
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proficiency in R or Python and version control systems like Git. Familiarity with spatial and statistical libraries (e.g. INLA, PyMC, scikit-learn, GeoPandas). Proven ability to work independently. Demonstrated
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opportunity to grow your skills in data visualisation, SQL and Python. We encourage applications from candidates who have experience from both within and outside of the Higher Education sector where they can
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formats (DICOM, NIfTI) and image preprocessing tools (e.g., MONAI, SimpleITK). Excellent programming skills, demonstrated through available code or projects, with proficiency in Python and deep learning
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, registers and other clinical studies Knowledge and practical application of various statistical packages, such as R and Python Ability to adapt and/or develop statistical and machine learning methodology
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, perinatal mental health, child health). High degree of competence in standard medical statistics and in using statistical software packages (e.g. R, Stata or Python). Experience working with large-scale
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, Python Track record in research outputs, including publications and research dissemination * Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award