95 computer-"https:"-"APOS-UFFICIO-CONCORSI-DOCENTI" "https:" "https:" "https:" "J. F" positions at Ulster University
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generator (Python toolkit), evaluation metrics suite, and academic papers in top finance and information systems venues. We welcome applicants with backgrounds in computer science, data science, or
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areas and now wishes to further expand understanding and application of Comprehensive Innovation. This research aligns with the innovation goals in the Programme for Government 2024–2027 and the Minister
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peacebuilding, conflict or the welfare state) or involve other disciplines, including but not limited to peace and conflict studies, social policy, political science, computing and film. A PhD may only be
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Development of smart clothing for physiological monitoring of children with heart conditions at home
programme. Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part
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as part of TRACE (Technological Revolution towards an Agri-food Circular Economy), a €5.89m cross-border project supported by the European Union’s PEACEPLUS Programme and managed by the Special EU
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that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme. Applicants who already hold a doctoral degree or who have
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Summary Applicants are invited to undertake a 3 year PhD program in partnership with a global leader in blood- and cell-based therapies (Terumo Blood and Cell Technologies Ltd). This opportunity
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, financial technology, policy analysis, or academia. Ideal candidate: Background in computer science, data science, finance, economics, or related quantitative fields. Strong programming skills (Python/R
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, and high-field NMR, using Ulster’s state-of-the-art facilities and Northern Ireland’s High-Performance Computing (NI-HPC) resources. You will gain skills in: Generative AI for structure prediction
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to accelerate the growth of existing neoplastic lesions (Mason 2009). These complexities highlight the need for sophisticated interdisciplinary approaches. This research programme will integrate artificial