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work environment Learn more about CQT at https://www.cqt.sg/ Job Description The CQT S14 team is looking for candidates with strong background in Software Engineering, Computational Physics or Computer
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-cell transcriptomics, or spatial tissue profiling data, and are keen to develop new methods, for example using machine learning. You have a proven track record of independent research funding and high
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computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The subject area concerns
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: office space, computer equipment, access to institutional digital resources, and the possibility to acquire pedagogical and scientific materials (books, software, licenses, etc.). The recruited candidate
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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for advancing the teaching of Statistics and Data Science and for the excellence of our undergraduate program, with large numbers of majors and popular joint programs in statistics and machine learning and
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to machine learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You
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sheet evolution, methane hydrate fluxes, or applying machine learning to geosciences to reconstruct glacial histories and project future ice sheet behavior. Please read this interview for more details
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through applied research programmes. Faculty in the ICT Cluster undertake funded industry-relevant research, teach courses in Computer Science, Computer Engineering, Information Security and Software
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Computer Programming · Ethics and Policy Questions: Genomics, Healthcare and Big Data · Introduction to Applied Data Analysis · Advanced Concepts in Computer Programming