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)) models are used at all stages of pre-clinical and clinical development, but they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a
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Master’s degree (preferably with a merit or distinction) in a social, biological or mathematical subject, or computer science. UKRI Minimum Stipend Research Training & Support Grant Institutional & CDT
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they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a laborious task where highly qualified staff spend large amounts of time. Aims
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for vulnerable populations. The ideal candidate has: Bachelor’s degree (first/upper second or equivalent) in Complex Systems, Network Science, Data Science, Computational Social Science, Physics, Mathematics
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AI has the potential to revolutionise healthcare, providing tools for fast and reliable analysis and interpretation of medical data. For instance, many deep learning models for medical image analysis have been recently developed and deployed in the clinic, assisting doctors with diagnosing and...
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, or higher) degree in Mathematics, Computer Science, Statistics, Engineering, Physics, or related STEM areas. Scholarship: The studentship is for 3 years and will provide an annual tax-free stipend of £20,662
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prediction. This project is a collaborative effort between the School of Computing & Mathematical Sciences (CMS) and the School of Engineering (SoE) to utilise expertise and facilities between two schools
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(with Merit or Distinction), in a related field such as (but not limited to) Engineering, Physical Sciences, and Mathematics. Experimental experience would be an advantage but not required as full
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Faculty of Computing, Mathematics, Engineering & Natural Sciences Funded PhD Project (UK or International Students) Funding provider: Northeastern University London (NU London) Subject areas
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to power engineering, mathematics, computing and energy economics. The successful candidate will have excellent understanding in the fields of power system operations and economics. Experience in data