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Field
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next-generation machine learning (ML) models that are both data-efficient and transferable, enabling more reliable catastrophic risk prediction, defined as the probability of exceeding critical safety
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or reinforcement learning, and good programming skills in Matlab and/or Python. You will have completed an undergraduate degree or MSc in a quantitative discipline. The Humphries’ group (https://www.humphries
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who could help with general course delivery, project supervision and marking of assessments. The post holder will teach undergraduate and computing modules within the School of Computing and Engineering
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that developments are well understood and embedded. To apply electrical/electronic design skills to create a prototype including circuit analysis, computer aided design and complex simulation tools, e.g. MATLAB/SPICE
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analysis (Excel, R, Python, Prism etc). D4 Knowledge of applying artificial intelligence and/or machine learning approaches to biological image analysis or data interpretation. Experience Essential E1
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modelling, multimodal neuro-imaging and physics-informed machine learning to improve assessment of glioblastoma treatment response. The candidate will also be expected to contribute to the formulation and
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machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. About the Role The post is funded
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team of 12 technical staff. The mechanical workshop has a range of machinery including conventional workshop equipment (lathes, mills etc.) CNC machines, 3D printers and other tooling. The role holder is
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collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI
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of knowledge in the subject of Robotics to develop research in the field, e.g., robot design, control and mechatronics; 4. Publication record in robotics and machine learning, e.g., ICRA, IROS, RSS, CoRL, T