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engineering, or related discipline. Documented expertise and an established track record in machine learning across different data domains of mental and/or neurological disorders. Experience in analysing high
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Charter, Stonewall Diversity Champion, and Disability Confident Employer. We are also proud signatories of the Armed Forces Covenant. Further Information For informal enquiries, contact Dr Rupam Das
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groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
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background in mathematics, statistics, population genetics, phylogenetics, epidemiological modelling, or machine learning. Highly motivated candidates with some, but not all, of the skills requested will be
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learning and health data science research and a strong interdisciplinary research culture. This post is full-time (35 hours per week), however, we are open to considering part-time or flexible working
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Lives with Linear Accelerators) project, which aims to leverage technologies developed for particle physics, computer vision and robotics into a novel end-to-end radiotherapy system as an essential
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computing, computer architecture, programming models and high performance computing. These are your qualifications: Must-haves: Completed doctoral/PhD studies in Computer Science or a closely related field
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) to organize, curate, and explore large-scale experimental data using a variety of data scientific approaches. Experience with or a strong interest in high-throughput geno-/phenotyping datasets and motivation
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bioinformatic analyses of large datasets Presenting your work at national and international conferences Working alongside a range of cardiovascular researchers to enhance your professional development
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researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state-of-the-art results in many applications. As a leading