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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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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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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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vitro cellular assays. Experience in using mouse disease models is also desirable. Scientific knowledge in the areas described above equivalent to PhD* level is required. The post-holder will possess
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pathways. You will also contribute to a future i4i application and help prepare dissemination materials for NHS and industry audiences. About you You will hold a PhD* or equivalent professional qualification
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About MINDS Centre for Doctoral Training The Machine Intelligence for Nano-Electronic Devices and Systems (MINDS), is a very successful £5M Centre for Doctoral Training (CDT) funding around 50 PhD
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be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title of Research Fellow will be applied upon completion of PhD. Prior