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practices using a combination of numerical modelling, field-based research, data analysis and physical experimentation. You will contribute to: Developing and applying numerical models to investigate
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laboratory and technical skills, with sound knowledge of research methods and a high level of accuracy and attention to detail. Strong organisational, computing and data management skills, including
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and/or computing, with the ability to engage credibly with technical and academic stakeholders and understand emerging industry and workforce needs. Highly developed leadership and stakeholder
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with ORSR. This PhD explores how fun operates as a core experiential concept shaping the quality of youth sport. Using both qualitative and quantitative methods, it will map the dimensions of fun as
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workplace observation; and (4) a mixed-methods synthesis producing a transferable, policy-relevant model of employer-led disability employment. The candidate will be supervised by Associate Professor
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workplace observation; and (4) a mixed-methods synthesis producing a transferable, policy-relevant model of employer-led disability employment. The candidate will be supervised by Associate Professor
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community-based correctional supervision known as “assisted desistance,” which centres on supporting the social and psychological processes involved in behaviour change. The project uses mixed methods
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to 3.5 years (full-time). Access to academic and industry expertise through joint supervision. A supportive environment to learn leading-edge research methods and become an expert in your area. The
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teaching and committed to preparing students for successful careers in law and related fields. You are confident using contemporary teaching methods and digital learning technologies, and you are
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or practitioner who is passionate about teaching and committed to preparing students for successful careers in law and related fields. You are confident using contemporary teaching methods and