19 phd-in-computer-vision-and-machine-learning Fellowship positions at RMIT University in Australia
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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scripting for simulation and data analysis, along with experience using high-performance computing environments, is required, and experience using structure prediction and/or machine learning methods is
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or implementing deep learning approaches on existing clinical systems). Experience and interest in grant writing would be viewed favourably. To be successful in this position, you will have: A PhD in a relevant
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- delivering a broad range of programs in Business, ranging from Certificates up to PHD levels. Many programs articulate between Vocational Education and Higher Education, creating pathways for further study
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postgraduate research students. Ability to contribute to the teaching and learning program in a relevant field. Qualifications: Mandatory: PhD in Ecotoxicology or Environmental Science or in a relevant field
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and the School of Computing Technologies to advance research on bushfire evacuation and emergency planning and preparedness in hazard events. You will support the research aim and objectives of the ARC
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salary and 17% Superannuation Based at one of the RMIT’s Melbourne campuses (City, Brunswick or Bundoora) About the Program Each year, RMIT brings on the world’s best and brightest researchers and teams
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. As your experience grows, you’ll take on more responsibility and contribute more independently to the research program. We welcome applicants at either Level A (Research Assistant) or Level B (Research
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Overview: RMIT Europe, in collaboration with RMIT University, is looking for a Postdoctoral Fellow to join the AuSpire Program. This position will focus on Regenerative Design Interventions in
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. Qualifications and requirements A PhD in Engineering or Computer Science with relevance to the outlined research area. A first degree in Engineering with research experience in creating digital twins or digital