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third largest university by intake in Singapore. SIT’s mission is to innovate with industry, through an integrated applied learning and research approach, so as to contribute to the economy and society
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 11 hours ago
& Computer Engineering Work Location EPIC Vacancy Open To All Candidates Position Designation Post Doc Employment Type Temporary - Part-time Hours per week 40 Work Schedule Pay Rate $48,000 - $53,000 Minimum
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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic
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Qualifications: Knowledge of kinetic modeling and/or machine learning interatomic potentials. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment
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People from Deepfakes Project. We are looking for a software/machine learning engineer (or similar) to work in an interdisciplinary team reporting to Dr Sophie Nightingale (Principal Investigator
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surface science. Preferred Qualifications: Knowledge of kinetic modeling and/or machine learning interatomic potentials. Background Investigation Statement: Prior to hiring, the final candidate(s) must
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mathematicians and computer scientists at the University of Southampton, the University of Oxford (lead node), Imperial College London, Queen Mary University of London, Durham University, and the University
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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dataset, GroupLens Research. grouplens.org [8] Statlog German Credit Data, UCI Machine Learning Repository. archive.ics.uci.edu [9] ERASER Benchmark, ERASER Project. eraserbenchmark.com [10] e-SNLI Dataset