436 data-"https:" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" "UCL" "UCL" Fellowship positions in Singapore
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an emphasis on technology, data science and the humanities. We are seeking accomplished and highly motivated Research and/or Senior Research Fellows to join an Industry Alignment Fund - Pre-Positioning (IAF-PP
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discipline (statistics, mathematics, computational biology, data science). Strong programming skills (R preferred) Statistical competence (Bayesian is advantageous) Please email the PI at ephdbsl
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description; A detailed curriculum vitae; 2 published articles or writing samples; and 3 reference letters. We regret that only shortlisted candidates will be notified. For further information about RSIS
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Science & Engineering, Chemistry, Electrochemistry, or Data Science/AI with a strong background in materials applications Technical Skills & Knowledge Experience in membrane fabrication and nanomaterials
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Supervise the collection and maintenance of clinical trial documentation, including data records and equipment maintenance logs Ensure compliance with clinical inventory management procedures Develop and
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(DoE) plan Plan and execute experiments Capture and analyse data Resolve technical problems Perform technical research and technical report writing Requirements: PhD in Mechanical, Electrical and
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Key Phenotypic Definition and Evaluation, including molecular and biochemical bioassays Characterization of Genetic Control Cultivar and Lines Development Integration of Genomic Data into Cultivation
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threats (prompt injection, data leakage, tool misuse). • Design identity and authorization for AI agents (authenticated tool use, secure delegation, cryptographic logging). Key responsibilities • Lead
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reactions, or transport mechanisms. • Experience in data-driven modeling or machine learning applied to membrane materials or separation performance analysis is a strong advantage. • Candidates with strong
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psychology, cognitive science, human-computer interaction, communication science, or a related field. Strong background in psychological research methods (e.g., behavioral, experimental, interviews, mixed