106 machine-learning-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in Singapore
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Responsibilities: Conduct research in Systems Biology to study cell signaling Perform large-scale signaling analysis or protein-interactome analysis Utilize machine learning-based biological data mining and analysis
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-Laplacian, discrete Ricci curvature) to characterize and model biopolymers such as DNA and RNA. Develop simplicial models for molecular representation, featurization, and learning, particularly in the context
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, climate-driven changes in pollutant dynamics, and associated health impacts by developing and applying deep-learning approaches to enhance air quality predictions and long-term projections under diverse
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-up phase and loss of skillset following study closure, as in typical trial setup. The Network will continuously develop its capabilities, quality and efficiency by learning from and collaborating with
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of 15+ years. Working at CDPT provides exceptional personal development opportunities in a vibrant international environment (Learn more at www.nanophotonics.sg ). No application deadline is set as the
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contributing to joint publications. Assist in mentoring and guiding graduate students in their research projects related to mathematical logic. Teach or tutor basic undergraduate courses for the division Job
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of teaching modules linked to current research themes, enriching academic programmes and promoting a collaborative learning environment. Uphold exemplary standards in record keeping, data confidentiality, and
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organizational and interpersonal communications with excellent written, oral communication and computer skills. A team player who is able to prioritize, multi-task and work collaboratively in a diverse workforce
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acquisition of lab consumables. Mentor junior researchers and teach organic chemistry lab skills, oversee lab safety. Present research progress in group meetings and private meetings. Organize results
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for a motivated and experienced Programme Manager to join the Centre for Holistic Initiatives (CHILD) for Learning and Development, Yong Loo Lin School of Medicine, National University of Singapore. CHILD