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and develop and maintain subscriber relations. Required Qualifications Experience in coordinating projects. Strong computer skills in the use of word processing, spreadsheet, presentation applications
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, Imperial College London, Ashoka University, the Communicable Diseases Agency Singapore (CDA), the National Environment Agency Singapore (NEA), the Machine Learning & Global Health Network (MLGH), and wider
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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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advanced data science methods, including statistical modeling and machine learning approaches Developing and applying novel causal inference methods, such as target trial emulation and causal AI frameworks
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geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and geospatial data analysis techniques to large Earth Observation datasets. • Produce high-quality
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/26. Preferred Qualifications: Strong background in algorithms, human-computer interaction (HCI), and software engineering. Experience in robotics systems, interactive or intelligent systems, or AI
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, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases
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analyze next generation sequencing data from collaborating laboratories and provide detailed report on results and interpretation. Independently implement latest machine learning algorithm to interpret
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. • Contribute to interdisciplinary research projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep
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biology and/or cell/organismal work. Familiarity with Drosophila handling (sorting, anesthetizing, setting crosses) or a strong willingness to learn quickly. Basic computer skills for data entry and