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Field
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quantitative data and relevant software (Stata, R, Python, or similar) would be advantageous. This is a part-time (32% FTE, 12 hours per week) fixed-term post until 28 February 2027. The Department of Social
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bootstrap inference for large datasets, variable-length time intervals and vectorised algorithms — and implement it in well-engineered, open-source R and Python packages (including SEQTaRget and pySEQTarget
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languages used in data integration and backend development (e.g., Python, Java, or equivalent), with a portfolio of relevant work developed collaboratively with source control (e.g. Git). Essential Interview
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Multiphysics Co-Simulation Engineer - KTP Associate (Full Time, Fixed term up to 24 months duration)
at Harper Adams University. The Associate will develop and validate physics-based simulation models, write high-performance C++ and Python code to integrate simulation and control environments, build and
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to work in a highly technical and collaborative academic environment, using modern software engineering practices and technologies including Python, TypeScript and React. You will also have the opportunity
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, computer science, or a related field Strong analytical, quantitative, and coding skills (particularly in Python) Experience handling and analysing large-scale biological datasets Track record of writing papers as
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science related discipline. You will possess established expertise in data analysis including statistical programming (e.g., STATA, RStudio, Python). You will demonstrate previous experience of contributing
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photometry and/or time-series analysis. Research experience in observational astronomy, demonstrated through publications appropriate to your career stage. Solid programming skills (e.g., Python) and
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expertise in at least a few from the following areas: Programming (C++, Python, etc) Machine Learning / AI Computer Vision Medical Image Analysis Prior experience in medical applications and medical data
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knowledge of signal processing, imaging, electronics, instrumentation, or medical device-related development. Hands-on experience in programming, preferably in Python, MATLAB, C/C++, or similar environments