13 experience-design-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" "Computer Vision Center" PhD positions at Flinders University
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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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. Candidates with a background in public health, epidemiology, health services research, biostatistics, and/or data analytics are encouraged to apply. Previous experience working with big data in R, SAS or
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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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(at least AQF Level 8), including a research component of at least 6 months’ full-time study achieving Distinction (75%) OR including evidence of equivalent research experience, such as a substantial
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equivalent qualification (at least AQF Level 8), including a research component of at least 6 months’ full-time study achieving Distinction (75%) OR including evidence of equivalent research experience
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evidence of equivalent research experience, such as a substantial firstauthor refereed publication or track record as an investigator on a competitive grant. • Applicants must be available to commence
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organisation or Aboriginal Liaison Officer that recognises you as an Indigenous person. From institutions that are unlimited institutional members of NAFEA (see https://nafea.org.au/membership/unlimited
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Description Flinders University is seeking motivated Honours and PhD candidates to join projects aligned with EMRNet’s objectives in energetic materials design, manufacture, testing, environmental
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successful candidate will design, fabricate, and characterise wearable and/or biosensor devices for physiological or biomolecular sensing. Depending on the candidate's interests and background, the
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Australian Health and Medical Research Institute (SAHMRI), and industry partner Natural Factors Australia. The overarching aim of our research program is to generate evidence that informs the design of