127 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UCL" Fellowship positions at National University of Singapore
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imaging, head & neck imaging) and development of novel imaging techniques (nuclear and molecular imaging, computational imaging, etc). With the formation of the National University Health System (NUHS
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and reproducible outcomes that align with the project's objectives. Supervising and mentoring undergraduate, postgraduate students, and junior researchers, fostering their professional development and
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and qualified Research Fellow to join our research team on the project titled “Development of 3D Vegetation Quality and Intensity Indices”. This project specifically looks at the processing and
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related area. The candidate must have excellent synthetic and engineering skills and good communication skills. The candidate sought to work on projects related to the development of synthetic organic
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related area. The candidate must have excellent synthetic and engineering skills and good communication skills. The candidate sought to work on projects related to the development of synthetic organic
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• Develop and implement generative AI models for urban landscape planning and design • Interpret and analyse data • Collaborate with other team members to conduct interdisciplinary research • Publish
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resilience to stressors in fish. The aim will be to integrate technology to develop the knowledge base for understanding stress resilience behaviours in Asian Seabass in farm conditions using laboratory model
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resilience to stressors in fish. The aim will be to integrate technology to develop the knowledge base for understanding stress resilience behaviours in Asian Seabass in farm conditions using laboratory model
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) at the National University of Singapore (NUS) is a leading multi-disciplinary institute devoted to developing new paradigms for understanding biological functions in health and diseases from the perspective of cell
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Responsibilities Develop and implement Python‑based AI/ML models (e.g. LSTM or time‑series models) to predict long‑term properties of bioactive materials. Conduct independent testing on restorative and bioactive