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professional networks. Candidate’s profile Knowledge of quantum computing and an understanding of challenges of building large-scale systems Programming skills in Python A good Bachelor’s Hons degree (2.1
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requirements for our PhD programme . Skills in Python, C++ or ROS are preferred. How to apply Applications should be submitted via the Robotics and Autonomous Systems PhD programme page. In place of a research
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profile We welcome applicants with backgrounds in computer science, applied mathematics, or engineering. Essential: strong Python, deep learning experience (PyTorch), and foundations in calculus/linear
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proficiency in three of the items in the following list: - Fluent programmer (e.g., python or other) - Fundamental of finite element analysis and experience with FEA software
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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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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks
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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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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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equipment (e.g., 3D scanning, surface inspection). Familiarity with data analysis tools (e.g., MATLAB, Python, or similar) and basic knowledge of machine learning is an advantage. Familiarity with research
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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