406 data-"https:"-"https:"-"https:"-"https:"-"UNIVERSITY-OF-HELSINKI" PhD positions in United Kingdom
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TypeFixed-termWorking TypeHybridAvailable for SecondmentNoClosing Date30-Apr-2026JD_Param11NoJD_Param12No Two 3.5 year PhD studentships in Artificial Intelligence in Medicine, or Health Data Science, funded
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | 3 months ago
function in the Safety and Surveillance group. Within a week of working here, your day could look like this: help shape the UK Government’s premier data-driven research service. You will participate in and
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Engineering, Biomedical Engineering, Physics/Medical Physics, Materials Science/Engineering, Chemical Engineering, Data Science/Signal Processing, Biomedical Science, Biological/Human/Life Sciences, etc.) and
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energy demand. Combining applied mycology, food safety modelling, precision agriculture and Net Zero energy systems, the research will deliver energy-efficient, data-driven grain storage solutions
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to provide the following information in the ‘Further Details’ section: A Personal Statement: one side of A4. The studentship code in the ‘Studentship/Partnership Reference’ field:MSP124 In the ‘Supporting
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Data is more valuable than oil, so it has been said. Quantum computing offers new unusual datasets thereby presenting new opportunities for AI approaches. Quantum computing is raising the prospect
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wellbeing . Further Information This is a full-time fixed-term post for 3 years. There can be some flexibility with the start date dependent on the circumstances of the candidate, but this post must start by
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highly desirable. Experience with green infrastructure, nature-based solutions, bioretention/rain gardens, or environmental data analysis will be an advantage. Enthusiasm for field research, the ability
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, stormwater/SuDS design, soil-plant-water interactions, or plant ecophysiology is highly desirable. Experience with green infrastructure, nature-based solutions, bioretention/rain gardens, or environmental data
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with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from