Dr David Klyne

Senior Research Fellow

School of Health and Rehabilitation Sciences
Faculty of Health and Behavioural Sciences
d.klyne@uq.edu.au
+61 7 336 54569

Overview

David M. Klyne PhD, MSc (MolBiol), DPhty, BAppSc) is a Fulbright Scholar and Research Fellow within the Centre for Clinical Research Excellence in Spinal Pain, Injury and Health. There he leads an international team of researchers that probe the bio-psycho-social mechanisms that underlie pain and the transition to chronicity. His niche is in understanding the neuro-immune pathways involved and how they can be targeted with interventions using a blend of basic and clinical sciences and his skills and knowledge gained through his four degrees – neuro-immunology (PhD), molecular biology (Master), physiotherapy (Doctorate) and applied sciences (Bachelor).

David has received numerous national and international research awards that span basic and clinical sciences. These include the premier international award for spine research (ISSLS Prize) on two occasions – in Basic Science (2019) and Clinical Science (2018). In 2019, he was awarded a postdoctoral Fulbright Fellowship to continue his work elucidating the role of sleep in chronic pain at the Lewis Katz School of Medicine (Temple University), in the USA. He was also one of ten Australian scientists to attend the Lindau Nobel Laureate Meeting in 2019, and has received more than $90K in research prize money and $11.5 million in research funding.

Research Interests

  • Acute to chronic pain
  • Neuro-immunology
  • Sleep
  • Chronic pain prevention and rehabilitation

Qualifications

  • Doctor of Philosophy, The University of Queensland
  • Master of Molecular Biology, The University of Queensland
  • Doctor of Physiotherapy, Bond University
  • Bachelor of Applied Science, Queenland University of Technology

Publications

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Supervision

  • Doctor Philosophy

View all Supervision

Available Projects

  • We are seeking PhD students with a background in biomedical and/or rehabilitative sciences to join our team to contribute to a body of work that aims to identify if and how sleep influences pain. Projects will involve the measurement and analysis of sleep in the “real world” to understand how daily variations in sleep – one of the most important, yet modifiable health behaviors – drive the day-to-day “waxing and waning” of back pain. The work will involve a multidisciplinary team to address this challenging issue.

    Essential criteria: An undergraduate degree with first or second class division 1 Honours in biomedical science, physiotherapy or a related discipline; eligibility for admission to the PhD program at The University of Queensland; knowledge of pain physiology; experience with statistical programs for data analysis; excellent communication skills (written and verbal) in English.

View all Available Projects

Publications

Journal Article

Conference Publication

Other Outputs

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • We are seeking PhD students with a background in biomedical and/or rehabilitative sciences to join our team to contribute to a body of work that aims to identify if and how sleep influences pain. Projects will involve the measurement and analysis of sleep in the “real world” to understand how daily variations in sleep – one of the most important, yet modifiable health behaviors – drive the day-to-day “waxing and waning” of back pain. The work will involve a multidisciplinary team to address this challenging issue.

    Essential criteria: An undergraduate degree with first or second class division 1 Honours in biomedical science, physiotherapy or a related discipline; eligibility for admission to the PhD program at The University of Queensland; knowledge of pain physiology; experience with statistical programs for data analysis; excellent communication skills (written and verbal) in English.