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of Singapore's research and innovation ecosystem and aims to support the development of a sustainable, climate-resilient, and healthy city through data-driven design and policy-relevant research. The programme
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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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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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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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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
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resolution. This PhD offers the opportunity to conduct cutting-edge research with direct industrial impact, combining fundamental fluid mechanics with modern data-driven techniques. The successful candidate
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. To view the job description and person specification, please click here. For further information and informal enquiries regarding the role, please contact Dr. Mark Kasumovic via mark.kasumovic
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the network, and every synapse is updated, on every epoch. Recent work has begun to challenge both halves of this independently. Progressive Data Dropout has shown that progressively reducing the training set