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of machine learning, simulation-driven testing, and iterative calibration based on real-world datasets. Contribute to scholarly publications, technical documentation, and progress reports required by funding
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mission is to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society. Singapore is the small city with a big dream. We are home
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organoids will be plus. Dry lab: Highly motivated candidates with a PhD/MD degree in bioinformatics, genome science, systems biology, biomedical informatics, computational biology, machine learning, data
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under uncertainty, and machine-learning-enhanced autonomy for Advanced Air Mobility. The anticipated start date is Fall 2025 or Spring 2026. Responsibilities include: Conducting advanced research in GNC
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optimisation and/or machine learning in control About the opportunity The successful applicant will become part of a collaborative and forward-thinking research team working across decision and control theory
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Simulation group to apply classical Molecular Dynamics and Machine Learning approaches for development of a new class of hybrid polyphenol-lipid nanoparticles with tuneable internal structure and exploration
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position under the supervision of Dr. Chris Smith. Our new lab in Evolution, Ecology, and Behavior investigates machine learning approaches for population genetics. Our research integrates custom neural
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of artificial intelligence and behavioral neuroscience. This individual will join our interdisciplinary team of computer scientists and behavioral neuroscientists seeking to identify the mechanistic and
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and/or digital culture). In addition to conducting their own research, supported by faculty mentorship, the Fellow will be expected to teach two courses per year: one lower-level course, such as
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- Life Sciences: Genomics, precision medicine, bioengineering, and health data science - AI and Digital: Machine learning, robotics, digital health, and cybersecurity - Defence and Advanced Manufacturing