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This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown
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Nuclear Science and Engineering Undergraduate Scholarship - Department of Defence | Australia | 5 days ago
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participating in domestic student recruitment and career events such as School Visits, Expos, Careers Fairs and University Open Days. Travel between campus and events will be by a university pool car, or
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Machine learning, dynamical systems theory, control theory, signal processing, network theory, neuroscience are all relevant and a student should have strong knowledge in at least one of these and a
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reinforcement learning. In International conference on machine learning (pp. 2107-2128). PMLR. - Péron, M., Becker, K., Bartlett, P., & Chades, I. (2017, February). Fast-tracking stationary MOMDPs for adaptive
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, UTS, UWA, Deakin, and Swinburne), and industry leaders such as Ford Australia, Seeing Machines, RACQ, The Department of Transport and Main Roads, National Transport Commission, Transport For NSW, and
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has a strong position within Australia and worldwide. To learn more about the School, click here . We are currently seeking to appoint Associate Lecturer (Education) x 8 (Level A) in Computer Sciences
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(20th of July 2026). Academic background: You must have an honours degree or demonstrated equivalent research expertise in computer science, machine learning, data science, human-computer interaction (HCI
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econometrics and machine learning, is highly desirable. You are well-organised and capable of managing multiple tasks to meet deadlines, with excellent written and verbal communication skills for producing clear