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/simulations. Key responsibilities will include but are not limited to: - Developing novel machine learning algorithms for the prediction of physical and chemical properties, infrared and mass spectra
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
: Bayesian Machine Learning – Led by Dr Thang Bui, this project focuses on sequential decision-making and bridging deep learning theory and practice. Applicants with expertise in probabilistic modelling
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Build and test predictive models using machine learning techniques Drive methodological innovation in neurophysiological data analysis Contribute to publications, grant submissions and independent
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An exciting postdoctoral position in method development for spatio-temporal medical data is available in the UiT Machine Learning Group at the Department of Physics and Technology . The positions aim is to
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aspects of predictive modeling. A Ph.D. in bioinformatics, genetics, statistics, computer science, or a comparably quantitative discipline (e.g., mathematics, physics), or comparable research experience
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of Machine Learning techniques. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation: the first phase comprises the Academic Evaluation (AC), based
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qualification/experience in a related field of study. The successful applicant will have expertise in statistical modelling, epidemiology or machine learning and possess sufficient specialist knowledge in
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig economies and prediction markets. Opportunity to supervise research students and work as part of a
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projects on metabolic diseases * Develop and apply machine learning models for biomarker discovery, patient stratification, and prediction of disease trajectories * Collaborate with clinicians