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Field
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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– in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in materials science, applied mathematics, computer science, or an AI related field completed within
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the computer science research conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings
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facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN researches and applies
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PhD degree in Telecommunication Engineering, or Electrical Engineering, or Computer Science/Engineering with a focus on SDN/NFV Strong expertise in SDN, orchestration, NFV, and container technologies
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2025 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within
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& Experience (specific to the project): PhD in Computer Science, Cybersecurity, Artificial Intelligence, or a related discipline. Strong research background in virtualisation, cybersecurity, AI or threat
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30 September 2028. This project is associated with an exciting new EPSRC/UKRI-funded Programme Grant entitled “Advanced Device Concepts for Next-Generation Photovoltaics.” This collaborative project
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frameworks and transformer architectures applied to biological sequences would be advantageous. You should have a PhD in bioinformatics, evolutionary biology, machine learning or similar. The post fixed term
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semiconductor materials. The position is available for a fixed term until 30 September 2028. This project is associated with an exciting new EPSRC/UKRI-funded Programme Grant entitled “Advanced Device Concepts