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Qualification Requirements: PhD (or equivalent) in clinical epidemiology, statistics, clinical endocrinology. Strong research experience in endocrinology and diabetes is desirable. Knowledge of biological sample
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. Knowledge of venture capital and investment opportunities. Experience in facilitating translation research. Excellent writing, communication, and organizational skills. Experience in working within
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-end technologies (e.g., Node.js, Python/Django/Flask, REST APIs, SQL/NoSQL databases) Demonstrated knowledge of AI/ML methods, such as supervised learning, NLP, or deep learning, with application
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authenticity, accountability, and integrity of digital content. Strong knowledge of machine learning and deep learning techniques, including machine unlearning, and AI testing. Ability to communicate complex
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teamwork and verbal, written communication skills Proven research ability as evidenced through a portfolio of publications and/or conference papers and/or patents. In-depth knowledge relevant to the project
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independently and flexibly in small and large teams Preferred: Knowledge of educational and psychosocial theories of human development Interest and experience in topics outlined in the Project Introduction
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knowledge in organic or polymer synthesis are strongly encouraged to apply or inquire. We regret that only shortlisted candidates will be notified. Hiring Institution: NTU
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the machines efficiently and safely. Conduct maintenance on the above machines, liaising with vendor engineers and trouble-shooting regular problems and issues. A strong crystallographic knowledge of single
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record and familiarity with the existing literature and research in the field of statistical machine learning, and deep learning or large language models. Possess sufficient specialist knowledge, research
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of gamma-ray or neutron measurement techniques Knowledge of gamma-ray spectroscopy using LaBr3(Ce), GAGG(Ce), or other modern scintillators Experience with Digital Pulse Processing for nuclear radiation