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to the advancement of AI applications in biological sciences. This role presents a unique opportunity to work with pangenomic datasets while exploring the application of Large Language Models (LLMs) and machine
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The purpose of this role is to support the work of the RICHeS programme at QUB providing research and access to archaeological and heritage science. The RICHeS Scientist (Research Fellow) will be a
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, supported by PEACEPLUS, a programme managed by the Special EU Programmes Body (SEUPB). The PEACEPLUS programme is co-funded by the European Union, the Government of the United
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machine learning/AI or cybersecurity, or both, as evidenced by a strong track record of publications in leading journals and conferences in relevant areas. Software programming skills. To be successful
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of the research theme. Some exposure to commercialisation market studies or IP processes. Strong skills in MATLAB Simulink and other modelling tools. Programming skills including software for programming DSP, PSoC