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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search
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decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both
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beginning in this role. We will require all candidates invited to interview to apply for NSTIx clearance. In this role you will: Design and test detection and estimation algorithms utilising artificial
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beginning in this role. We will require all candidates invited to interview to apply for NSTIx clearance. In this role you will: Design and test detection and estimation algorithms utilising artificial
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benefit society by advancing technologies that will underpin the design of the next generation of transport aircraft. Specifically, you will develop, test, and industrialise algorithms designed to simulate
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requirements We are looking for a candidate who meets the following essential criteria: A PhD (or be close to completion*) in Biotechnology, Engineering, Microbiology, or a related field or equivalent experience
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, University of Southampton. You will have a relevant PhD, Master degree or equivalent research-related qualifications in a health/ public health/ epidemiology/ healthcare or social science related subject, and
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the new technology works and compares with existing drugs with the aim of improving cancer treatments. You will be motivated, educated to PhD level in a relevant subject area and ideally have practical
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Medical Education and the Department of Civil, Maritime and Environmental Engineering. You will have a relevant PhD or equivalent research-related qualifications a health/ public health/ epidemiology