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self-harm rates. You will expand your data wrangling, analytical and programming skills on python and develop expertise in the fields of machine learning, epidemiology, big data analysis, and suicide and
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(ESBMC, CBMC, Z3, or similar) – either academic or practical. • Programming proficiency in C/C++, Python, and familiarity with software verification tool development. • Understanding of ML/NLP fundamentals
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and technology. Desirable (not essential): Research experience in sports medicine and technology (e.g. publication or final year project). Programming skills in MATLAB or Python. Application Procedure
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techniques (geomorphic mapping, TruPulse, DGPS/drone surveys), engineering geology methodologies (slope stability, rock strength assessment), coding (python/matlab data analysis and modelling) and transferable
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qualifications will be considered. Experience of using machine learning algorithms and toolsets, ideally in a research context. Strong programming skills (e.g., Python, Java, C++) An interest in physiological
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equivalent in a related discipline. This project would suit someone with: Experience with programming (Python, MATLAB), background in aerospace, computer science, robotics, or electrical engineering graduates
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, Urban Studies, Urban Analytics, Environmental Science, Computer Science, Architecture, or an appropriate master’s degree. Familiarity with Python/R programming, GIS and spatial analysis (e.g., ArcGIS
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programming (e.g., Python, MATLAB). Energy system modelling expertise with experience in academic research Preferred Skills: Educational background in Electrical Engineering, Computer Science, Renewable Energy
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Engineering or Computer Science. We would also like to see experience in: Machine Learning, Optimisation, Python, finite elements How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and
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environment Proven ability to use a scientific programming language such as python or MATLAB for signal processing A desire to improve therapies available to patients with neurological conditions Excellent