569 data "https:" "https:" "https:" "https:" "UNIVERSITY OF RIJEKA" PhD positions in United Kingdom
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supporting the setup, calibration, and running of laboratory experiments, including the preparation and configuration of sensors, data acquisition systems, and associated hardware and software components
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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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’) as the programme of study You will then need to provide the following information in the ‘Further Details’ section: A ‘Personal Statement’ (this is a mandatory field) - upload a document or write a
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and experimental data, the student will develop predictive models of strand displacement reactions in non-ideal settings, in collaboration with the other students within BIOHYBRITE. These areas include
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fees. See UKCISA for further information. Starting in October 2026. Later start dates may be possible, please contact Dr Lucia Florescu once the deadline passes. You will need to meet the minimum entry
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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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programme. Nationality restrictions Other eligibility criteria The proposed research project must be within the remit of EPSRC's research themes. Please see EPSRC website for information. Application
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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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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