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staff of around 120, including 66 permanent staff. It has a strong experimental component, with numerous prototype set-ups supported by both standard equipment and high-tech instrumentation
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focus groups; conducting data analysis; presenting the work at national and international conferences; spending 10% of your time on teaching-related tasks. What do you have to offer You have: a (research
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, and building on developments in camera technology through the FinVision project (https://www.plymouth.ac.uk/research/marine-conservation-research-group/fishing-and-aquaculture/finvision ), the student
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for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high-dimensional data. Develop modular
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also deal with the diffusive behavior of certain elements simulating fission products (FPs) and activation products within these materials. This thesis will study the properties of chromium-doped UO2
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analysis team, contributing to data generation, processing, and delivery. The project will address key challenges such as advanced backscatter mitigation, improved scale factor estimation, and advanced post
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deposition processes for transition-metal-based electrocatalysts. Investigate the activity, stability, and selectivity of the prepared materials for the oxygen evolution reaction (OER), hydrogen
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
leadership, data analysis, and interpretation of results. A substantial component of the role involves the analysis and integration of high-dimensional genomic and transcriptomic datasets, including DNA and
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for doctoral studies at the University of Helsinki (https://www.helsinki.fi/en/admissions-and-education/apply-doctoral-programmes ) and obtain a doctoral study right within the trial period of 6 months. Five
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, annotators, and underlying neural architectures. The ultimate goal is to produce argument mining tools that are more robust, generalizable, and fair, applicable to sensitive domains such as the analysis