120 coding-"https:" "https:" "https:" "Computer Vision Center" positions at Flinders University in Australia
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for applicants to also have: Honours/Masters degree in either Engineering, Computer Science or IT related fields. Experience in Deep Learning, Computer Vision, and Python programming Interest in
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collaborations across engineering and computer science. With a particular focus on growth areas including defence, sustainable energy, artificial intelligence and cybersecurity , you will help position the
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significant research and data registry. Working as part of a small, collaborative team, you will contribute to the accurate processing, coding, management and quality assurance of clinical data
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procedures. Assisting with qualitative and quantitative data management, including data cleaning, coding, analysis, and summaries of findings. This position makes a significant contribution to the
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). The PhD project would suit a student with a background in computational modelling or engineering. The student will develop computational models that simulate neural pathways for motion vision in
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STATA are preferred but professional development can be provided where necessary. The successful candidates will work under the supervision of Professors Maria Inacio ( https://research.sahmri.org.au
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academic merit and research potential, in alignment with College values of equity, excellence and social vision. Applications will be ranked (based on the NHMRC criteria for postgraduate scholarships
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, or Engineering. Candidates should be able to demonstrate applied coding and analytical skills (e.g. Python, R, SQL, or MATLAB) and an interest or experience in statistical modelling, machine learning
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; International candidates must also meet Flinders University Academic and English language requirements. https://www.flinders.edu.au/international/apply/apply-research-degree/eligibility Application
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student, researcher, tutor, research assistant or affiliate or have held such a position within the last ten years. Application Information Further information can be found on https://neaf.sydney.edu.au