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for healthcare and data systems. Responsibilities: Conduct research on large language models (LLMs), including their applications in code generation, data transformation, and medical AI. Design and implement
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systems and developing new design methods. Key Responsibilities: Conduct experiments on innovative structure systems Conduct numerical modelling Assess existing design codes Propose new improved design
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Responsibilities: To conduct systematic literature reviews (summarizing, coding, and organizing relevant literature). To compute different statistical analyses for the findings obtained. To contribute to research
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, assist the lecturer with grading and other course administration tasks, exam/test invigilation etc. Able to teach and/or support at least 3-4 BT/IS-coded courses, with at least 1-2 foundational courses
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-on experience in specific scope Familiarity with required scope (e.g. national codes and standards) Good written and oral communication skills (if applicable) Proficiency in hard skills / job-specific abilities
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, Nvivo Responsibilities: Working on literature searches, reviews and report writing Conducting meta-analysis on the literature searched Organising data collection Assist in analysis of data through coding
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replicability Assist in thematic coding and clustering of research findings Support scoping review, creation of summary tables, and conceptual maps. Contribute to writing methods and results sections following
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and a strong commitment to Software Engineering best practices, writing code that is clean, modular, and maintainable. • MLOps & Cloud Proficiency: Fluent in the essential MLOps toolkit, including Git
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, codes, and calculations with minimum oversight. • Perform simulations to assess various study design options and analysis approaches. • Monitor discretionary spending in a team to ensure that spending is
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Research Assistant (RA) will be responsible to, and work closely with, the Principal Investigator and study team members to ensure the successful completion of the non-coding RNA (ncRNA) biomarker discovery