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This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion
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testing strategies. About you The successful candidate will have: A Masterʼs degree and/or Bachelor’s degree in epidemiology, public health, health data science, health informatics, health economics
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-Based Modelling ✔ Data Science & Advanced Analytics with real-world SCADA data ✔ Renewable Energy Systems & Wind Turbine Engineering ✔ Industry Engagement & Research Commercialization ✔ Scientific Writing
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and/or Python, is highly desirable. Experience of collecting neuroimaging and/or wearables data from infants/children is also desirable. The project will be based at the Institute for the Science of
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. In this project, you’ll have the opportunity to be trained and become a proficient user of a range of advanced experimental techniques. For instance, you’ll learn how to use in-situ X-ray Computed
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Master in Epidemiology or Public Health with experience in medical statistical analyses, an understanding of Health Economics, knowledge of the strengths and weaknesses of scientific research, excellent
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, spanning domains from automotive and avionics to healthcare, increasingly rely on distributed and multi-layered control architectures. These systems comprise interconnected computing nodes, actuators and
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of collecting neuroimaging and/or wearables data from infants/children is also desirable. The project will be based at the Institute for the Science of Early Years (www.isey.org ) in London, UK. Supervision will
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according to how well they meet the following criteria: A first class or strong upper second-class undergraduate degree with honours in Engineering, Physics or Materials Science Excellent English written and
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of microlensing this is a one-off event, whilst self-lensing repeats on the orbital period of the binary allowing it to be distinguished. New citizen science projects are being led by Prof Middleton’s group (black