99 systems-science-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions at Monash University
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Primary supervisor Jesmin Nahar Research area Data Science and Artificial Intelligence Background Colorectal cancer is a major health challenge, and early detection and accurate risk assessment are
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Primary supervisor Mor Vered Co-supervisors Iadine Chades Research area Data Science and Artificial Intelligence Markov Decision Processes (MDPs) are frameworks used to model decision-making in
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Philosophy of Science - (HPS Volume 7) Philosophy of Statistics, P.S. Bandyopadhyay and M.R. Forster (eds.), Elsevier, [ISBN: 978-0-444-51862-0 {ISBN 10: 0-444-51542-9 / ISBN 13: 978-0-444-51862-0
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Primary supervisor Jesmin Nahar Co-supervisors Anyone from the Faculty who is interested. Research area Data Science and Artificial Intelligence Background Cardiovascular disease is a major global
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Philosophy of Science - (HPS Volume 7) Philosophy of Statistics, P.S. Bandyopadhyay and M.R. Forster (eds.), Elsevier, [ISBN: 978-0-444-51862-0 {ISBN 10: 0-444-51542-9 / ISBN 13: 978-0-444-51862-0
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Primary supervisor Jesmin Nahar Co-supervisors Anyone from the Faculty who is interested. Research area Data Science and Artificial Intelligence Background Cardiovascular disease is a major global
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Primary supervisor Mohammed Eunus Ali Co-supervisors Aamir Cheema Research area Databases and Distributed Systems Public transportation is vital for sustainable urban mobility, yet challenges like
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Primary supervisor Aamir Cheema Research area Databases and Distributed Systems This PhD project will develop intelligent, data-driven methods for integrating diverse autonomous vehicles, such as
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Primary supervisor Aamir Cheema Research area Databases and Distributed Systems This PhD project will develop intelligent, data-driven methods for integrating diverse autonomous vehicles, such as
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interest in genetics, computational biology, or data science. A background in statistics, computer science, or related quantitative fields will be advantageous. AIM 1 : Improve predictive performance