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Robotics to develop research in the field, e.g., robot design, control and mechatronics; Publication record in robotics and machine learning, e.g., ICRA, IROS, RSS, CoRL, T-RO, CVPR, ICML; Excellent verbal
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have: A PhD (or equivalent) in a relevant discipline (e.g., biostatistics, machine learning, computer science, clinical informatics, natural language processing). Strong skills in data analysis and
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large-scale speech and wearable data from participants in the GLAD Study cohort (https://gladstudy.org.uk/ ). Using large language models (LLMs) and acoustic analytics, they will uncover patterns in
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system may hold clues to how psychosis and other psychiatric disorders are caused and how people respond to treatments. We will investigate blood and cerebrospinal fluid from patients and use machine
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metabolism Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and
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of machine learning to metamaterials modelling Experience in modelling molecular interactions Experience in modelling of mass transport at the nanoscale Downloading a copy of our Job Description Full details
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communication skills Desirable criteria Experience in application of machine learning to metamaterials modelling Experience in modelling molecular interactions Experience in modelling of mass transport
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engineering, or related disciplines who are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models
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skills. Aware of the ethical issues around working with Big Data. Desirable criteria Experience applying advanced statistical or machine learning methods to complex datasets. Evidence of involvement in
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interaction. Within CORE, SAIR focuses on multimodal machine learning for human-centred embodied AI, specifically tackling challenges in multimodal perception, understanding and forecasting human behaviour, as