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experience: Essential criteria 1. PhD in computer science, AI or related area 2. Proven experience of knowledge engineering and semantic technologies such as knowledge graphs, ontologies, data
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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project is time limited and will end on 31/12/2027. Person Specification Essential Criteria: Qualifications A good first degree in an Engineering related subject. A PhD (or be close to submission) in Marine
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the successful software package VASP (Vienna ab-initio Simulation Package). Currently, the group consists of two full professors, one associate professor, several postdocs and about 10 PhD and master students
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posters locally and at national and international conferences, as well as participate in MRC grant’s research programme led by Prof Marco Fritzsche. You must hold a relevant PhD/DPhil (or be near completion
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will have a PhD in a relevant scientific discipline and sufficient specialist knowledge relevant to the project to be able to make a start on day one – we do not expect everyone to have all the skills
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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personality: Master in Computer Science, Applied Mathematics or equivalent qualification with a strong focus on Computer Science with excellent marks. PhD with focus on data mining Strong publication record
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the UKRI through the Frontier Guarantee Programme to Dr Jani R Bolla. The work is to be conducted in his lab in the Department Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying