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Doctor of Philosophy (PhD) graduate researchers, in which the primary data for the PhD thesis can be collected only in a field location (for example, a fundable project may require access to particular
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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technologies, AI and big data. Crop and soil health - resistance and integrated pest management (including AI-driven prediction) and improving the root-soil interface (carbon, water and nutrient availability
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criteria: Knowledge of the molecular basis of ageing, muscle physiology, or the circadian clock. Experience or strong interest in data science, machine learning, or bioinformatics. Exposure to high
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Dalton Building at Manchester Metropolitan University. You will develop skills in computational experimentation, financial data analytics, and systemic risk modelling, with extensive opportunities
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to: Develop automated computer aided design (CAD) and meshing pipelines to generate a library of arterial geometries representing common geometric archetypes (e.g. curved vessels, bifurcations, side branches
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project meetings / secondments Collaborate with external industrial and academic partners Disseminate research findings through publications and conference presentations For further information please
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and organisations, which has been documented by a list of outstanding placements . Course organisation Information can be found on our website . PDF Download International elements International guest
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experimental development at the NQCC. Supervisors: Dr Eran Ginossar and Alexander Owens Entry requirements Open to candidates who pay UK/home rate fees. See UKCISA for further information. Starting in October
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17 Jan 2026 Job Information Organisation/Company University of South Bohemia Research Field Environmental science Environmental science » Earth science Environmental science » Ecology Mathematics