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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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Apply now Job no:584181 Work type:Casual Location:Melbourne - Burwood Categories:Arts Dr Mia Martin Hobbs seeks a PhD candidate for her DECRA project ‘Race, Gender, and Violence in Western
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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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market, Role of EVs in the grid, Power System Stability Analysis Using Machine Learning Techniques and more. Eligibility Requirements: Applicants must be Australian citizens or Permanent Residents
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the optical-to-radio wavelength range, from major surveys and space telescopes (e.g: Gaia, SDSS, JWST, Hubble, Roman, Rubin-LSST). These are analysed using advanced machine learning and data-driven methods. My
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We are seeking a motivated PhD candidate to work on unsupervised music emotion tagging within the broader field of affective computing. The project aims to develop reproducible machine learning
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, and a PhD research program with over 120 students. 40 academic staff conduct experimental research in many areas of Psychology, including behavioural and cognitive neuroscience, perception, learning
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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modelling, or machine learning). Proficiency in statistical programming (e.g., R, Python, Stan, or similar). Experience developing and managing longitudinal studies. Evidence of contributions towards