470 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" PhD positions in United Kingdom
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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. Building upon existing expertise in porous media modelling within the Thermo-Fluids Research Group (UoM), the project will analyse and volume-average these data to develop targeted refinements or propose
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identifying and prioritising conservation action especially challenging. This project aims to develop a low-cost, field-based, portable and easy-to-use Lab-on-a-Chip device for environmental DNA monitoring
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industrially-relevant human-made materials. This project will address key priorities in the microscopy sector by developing workflows that integrate cutting-edge imaging and characterization techniques and
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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project offers a unique opportunity to develop a cutting-edge genomic epidemiology toolkit for real-time fungal surveillance. You’ll optimize DNA extraction protocols using advanced enzyme-based methods
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of measles evolution and naming systems (nomenclature) to support public health identification of measles outbreaks/importation and ultimately, elimination. In this project you will learn to perform genomic
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reducing the environmental impacts of computational science. The tools and frameworks developed and maintained by the group are used internationally and include the popular Green Algorithms online calculator
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of experience in the development of sensors for healthcare applications; Dr Diganta Das; Stephanie Edwards and Andrew Peers. Loughborough University has an applied research culture. In REF 2021, 94% of the work
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport