614 data-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" Fellowship positions in United Kingdom
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high-level of independence and leadership the development of the new methodology and synthesis under the direction of Dr Mattia Silvi • Prepare high quality supporting information for publications
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Github • Using a range of computer systems to run fluid flow simulations and optimisation algorithms, including High Performance Computing architectures • Assist and mentor students and research group
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excellent communication skills, both written and presentation. Additional information Informal enquiries are welcome and should be made to Jack Sargeant on jack.sargeant@nhs.net Applications for job share
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2026 Background We are seeking a highly motivated researcher in statistics, geostatistics, data science, or a related field to join our research team in the Department of Applied Health Sciences
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of what data to analyse first, and whether to gather additional intelligence, potentially at the cost of delay or increased risk. Addressing this challenge is becoming increasingly urgent as both the scale
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omics techniques to bacterial isolates, or metagenomic samples from the clinic or environment. Able to perform downstream bioinformatics and data analysis (working with other post doc bioinformaticians
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/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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of what data to analyse first, and whether to gather additional intelligence, potentially at the cost of delay or increased risk. Addressing this challenge is becoming increasingly urgent as both the scale
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delivering the research goals of the group Conduct a research program, defined in agreement with the group Contribute to writing bids for research funding (including facility access) Analyse and interpret data
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at LSHTM. The post-holder must have a postgraduate degree in a relevant topic (ideally Medical Statistics or equivalent) and relevant experience in using regression models for data analysis and statistical