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of degradation pathways and shelf-life prediction. The aim of project is the safe integration of machine learning methods within the biopharmaceutical development process. This project offers an opportunity to be
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. The aim of project is the safe integration of machine learning methods within the biopharmaceutical development process. This project offers an opportunity to be at the forefront of interdisciplinary
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Health Regulations. Assist in project resource requirements and managing student projects. Job Requirements: Have a PhD Degree in Computer Engineering/Computer Science/Electrical Engineering or equivalent
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or machine learning methods Advanced knowledge of electronic healthcare records and their use in development and validation of risk prediction models Knowledge in application of econometrics in research
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To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in health data science, medical statistics or machine learning methods
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students. Selection criteria: • PhD/DPhil in a relevant field (or near completion). • Strong project management and communication skills. • Multidisciplinary and collaborative mindset
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students. Selection criteria: PhD/DPhil in a relevant field (or near completion). Strong project management and communication skills. Multidisciplinary and collaborative mindset. Commitment to EDI and
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quantitative data analysis: applied machine learning, statistical analysis, and handling complex data. Programming skills in Python and R are essential Experience in applying computational methods to research