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Apply and key information Summary This MRes project will focus on the development and investigation of the health benefits of sustainable marine derived lipids. In particular, the project will focus
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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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ensure that they have the right to work in the UK or be able to secure this through another means without the sponsorship of the University. Further information about sponsorship is available on the UK
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evaluation to assess the effectiveness of different interventions. This will involve collating and analysing qualitative and quantitative data; identifying, summarising and presenting insights to help
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machine learning with spectral data to enable rapid, non-destructive detection of food adulteration and fraud. Machine learning combined with spectral data can play a vital role in combating food fraud by
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technologies enable our students, staff, researchers, visitors, and partners to confidently and creatively use digital services, technology and data for the benefit of their learning, teaching, research or work
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, analysing and reporting of energy data to identify, investigate and quantify opportunities for energy and carbon savings. The post holder will develop and deliver presentations, briefings and reports
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these representations to guide the identification, by debate, of (non-)compliance to PRLs of LLMs and T2Is; O3) in the case of non-compliance, using information conveyed in the debates to enforce PRLs on LLMs and T2Is
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and interpret research findings and results from existing data Collect pilot data and demonstrate proof of concept for new methods Main Duties The responsibilities may include some but not all
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’, and to several ML-based projects at the British Antarctic Survey (BAS). There are also strong connections to the Institute for Data and Artificial Intelligence (IDAI) at UoB. Role Summary Implement and