12 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions at Queensland University of Technology
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The Centre for Data Science (CDS), the Australian Institute of Sport (AIS) and Queensland Academy of Sport (QAS) are leading a consortium of government and industry organisations in sports, sports and
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health, pharmacy, public health or health information management, or a related field, such as digital health, health informatics or psychology, with demonstrated experience in health settings Demonstrated
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statistical data science. How to apply Apply for this scholarship at the same time you apply for admission to a QUT Doctor of Philosophy . To apply, email Associate Professor Nicole White and include your
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expertise: Bioinformatics experience A PhD student with bioinformatics experience will generate and analyse complex microbiome sequence data to complement existing rumen microbiome datasets. Via multi-omics
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. An additional amount of up to $5,000 is available to support project costs, equipment or research-related travel for site visits, data collection, and/or conference attendance. Eligibility To be eligible
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of system and data confidentiality and complete any other requirements. Desirable skills: Experience in programming (C, python, or similar). Knowledge in machine learning or distributed systems. How to apply
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polymer chemistry or tissue engineering. Strong skill set for data analysis and interpretation, coupled with excellent written and verbal communication abilities. Ability to work effectively in a
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supported by an ARC Industry Fellowship, in partnership with Bush Heritage Australia. The student will work closely with ecologists and computer scientists at QUT and conservation managers at Bush Heritage
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and/or external study is obtained). Have an Honours or Master’s degree (or equivalent) in one of these areas: Engineering, Computer Science, Human Factors, Psychology, Data Science, Robotics, or a
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-products, multi-omics approaches, and/or opportunistic pathogens and AMR indicators. PhD-3 and 4 Strong quantitative/statistical data skills, understanding of water quality processes and experience/aptitude