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spaces and habits for them. This is a highly interdisciplinary project that combines computational modelling and behavioural science. The first part will be based on the use of state-of-the-art
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. A policy internship at a relevant organisation is embedded into this programme. Number Of Awards One Start Date 5th January 2026 Award Duration 3.5 Years Application Closing Date 30th September 2025
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requirements for your preferred programme, in addition to those specified by RADMA. Nationality restrictions This funding is available to all nationalities. Other eligibility criteria This award is available
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need to contact the project supervisor to discuss. Online applications are made via the 'Apply' button above. Please select Engineering Mathematics* on the Programme Choice page. You will be prompted
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Applications are invited for a Senior Researcher in Decision Analytic Modelling, working with Associate Professors Apostolos Tsiachristas and Brian Nicholson, on a research programme developing and
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 2 months ago
, environmental engineering/science, computer science, industrial or mechanical engineering, and decision science. The successful candidate will contribute to ongoing NSF-funded research projects during the initial
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Applications are invited for a Senior Researcher in Decision Analytic Modelling, working with Associate Professors Apostolos Tsiachristas and Brian Nicholson, on a research programme developing and
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an appropriate subject or a relevant Masters qualification. If your first language is not English, you will need to meet the minimum English requirements for the programme, IELTS Academic score of 6.5 (with
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of the largest Statistics departments in the world, with a thriving PhD programme and a long-established reputation for research activity of the highest quality, enhancing both the PhD student experience and the
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computational and machine learning approaches to integrate Oxford Nanopore (ONT) long-read data with bulk and single-cell RNA-seq profiles. The aim is to identify host-microbiome molecular signatures that drive