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Field
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and rigorous risk management. They will also need to leverage existing and bring new connections to solicit feedback and design the work for optimal pull through, in the following ways: (i) alignment
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skills for completing the project within the time frame international experience and network qualifications within the areas of creativity, innovation and commercialisation of research good teamwork
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on human behavior modeling related to video classification using deep learning networks for end-users. Work with other team members to develop and maintain software for maximum efficiency and usability
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Enhancement of AI/ML with in-network computing & processing Adaptation & optimization of AI/ML software libraries for non-conventional hardware architectures Physics-informed ML surrogates for efficient
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(e.g. CRISPR, homologous recombination, phage integration). Minimum two (2) years of experience with cloning, genome editing, enzyme and pathway optimization. Minimum two (2) years of experience with
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their advisors with calibrated tools to evaluate the outcomes of competing management decisions, thereby optimizing productivity, nutritional efficiency, animal health, and sustainability, particularly by
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management decisions, thereby optimizing productivity, nutritional efficiency, animal health, and sustainability, particularly by reducing net carbon emissions and refining antimicrobial use. The successful
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and methods, experimental design, and anticipated outcomes prior to initiating experiments. In addition, the fellow will establish and optimize pipelines for efficient genome editing in the emergent
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effects of urban greenery and develop a modelling platform to assess and optimize the cooling benefits of various types and configurations of urban greenery in Singapore Key Responsibilities • Conduct multi
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improvement, discovery trait research and methodology optimization to reach greater breeding efficiency. The general research technologies/methodologies and approaches are derived from plant breeding, genomics