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Field
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, financial technology, policy analysis, or academia. Ideal candidate: Background in computer science, data science, finance, economics, or related quantitative fields. Strong programming skills (Python/R
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mathematical background. Experience of image processing and analysis techniques and experience of coding (e.g. Python, Matlab and/or C++). Deep learning experience. Eligibility to obtain M.O.D Security
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, evidenced by peer-reviewed publications or equivalent research outputs. Experience working with spatial and/or spatio-temporal data. Experience using statistical programming languages (e.g. R, Python
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, particularly MRI, medical physics or computational data analysis (Python/R/MATLAB, machine learning, or bioinformatics) is highly desirable. Interested candidates should send a CV to michael.chappell
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, or other related academic discipline. Good programming skills (preferably Python). Background/work experience in Cyber Security, Machine Learning, and Finance would be highly beneficial. How to apply
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with statistics or programming in R/python/MATLAB desirable. Mode of study Full-time Start date 1 October 2026 Additional Funding Information This project is fully funded for 3 years. Funding includes
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Familiarity with use of Reference Managers Desirable Skills: Quantitative/Data Visualisation skills (Python?) Experience in data management Postgraduate or relevant research experience Works well within a team
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. Proficiency in deep learning frameworks such as PyTorch or TensorFlow. Experience with ROS / ROS 2 for real-robot software integration. Proficiency in Python and C++, with good software engineering practices
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Visualisation skills (Python?) Experience in data management Postgraduate or relevant research experience Works well within a team and independently Please note that unfortunately we can not accept Certificate
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to create working prototypes. You may be comfortable working with software such as Linux, ROS, Python etc. You will be part of a diverse team who are responsible for designing, building, programming, testing