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DPhil students, manage data analysis pipelines, and contribute to publications and grant writing. This post is ideally suited to someone aiming to secure a long-term fellowship and build an independent
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intelligence to use all the information in the electronic patient record to best identify who is at risk of deterioration. We will then investigate how to use this information to escalate the care of women in
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becomes essential. This project will focus on building a comprehensive digital twin of a future quantum computer to investigate how classical subsystems scale and interact, and how this scaling impacts
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lab has developed the OrthoFinder comparative genomic methods. OrthoFinder has become widely-used in comparative genomics research, it powers many popular databases of online genomic information, and
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follow up and recruitment of the children, at age 1 to 4 years, scheduling and conducting screening and study assessments, performing ultrasound imaging, and managing data entry and quality control. As the
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must hold, or be close to completion of a doctoral degree in a relevant field (e.g., data science, geography, environmental science, public health, economics). You will have experience relevant for food
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of experimental data. You will primarily support the insectary at the Jenner Institute aiming for the assessment of new target antigens as vaccine candidates for the Malaria Vaccine Programme using some of the most
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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on modelling of the transport, electrochemistry, and mechanics of next-generation lithium/air electrode materials and cell architectures. Using input data from experiments, the post holder will develop and
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will be expected to spend most of their working hours on site. Informal enquiries may be addressed to Chris Mitchell christine.mitchell@eng.ox.ac.uk Further information can be found at http