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benefit from the supervision of Co-I Dr Joseph M Barnby (Perth), Co-I Dr Michael Moutoussis (UCL), and Co-I Syeda Tahir (KCL). This role will provide you with the freedom to develop new and creative ideas
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’ Hospital in central London in the School of Biomedical Engineering & Imaging Sciences at King’s College London: https://www.kcl.ac.uk/bmeis . There is an unmatched infrastructure in place to support the
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discipline. Experience in developing complex models using real-world data, with strong programming proficiency in R or Python and version control systems like Git. Familiarity with spatial and statistical
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experimental chemistry, providing a supportive research environment. Applicants should have a PhD in Chemistry or related field, and extensive experience in python programming and machine learning models
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(or pending results) Proficient in using R, Python or similar programming language Experience of working with clinical or equivalent data. Experience in developing analytic pipelines. Desirable criteria
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with proficiency in Python, R, and tools relevant to multi-omics data analysis (e.g., CellRanger, GECKO, tINIT) Demonstrated ability to work independently, manage time effectively, and meet competing
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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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, 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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Diagnosis Industrial IoT and Edge Computing Good programming skills (e.g., Python, MATLAB, C++) and experience with system simulation. Experience with industrial field projects or familiarity with DCS/MES
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methodologies across MATLAB, Python, and/or R. Highly motivated and enthusiastic researcher with a strong and documented interdisciplinary interest in mental health Strong evidence of potential to build