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Postdoctoral Research Officer
  • Cutting-edge modelling of OCD brain dynamics
  • Exciting opportunity in a new and growing group
  • Attractive salary packaging & superannuation options

About QIMR Berghofer:

QIMR Berghofer is a world-leading translational medical research institute focused on improving health by developing new diagnostics, better treatments and prevention strategies, specifically in the areas of cancer, infectious diseases, mental health and chronic disorders. Based in Herston, Brisbane and working in close collaboration with clinicians and other research institutes, QIMR Berghofer is home to more than 600 scientists, students and support staff.

QIMR Berghofer Medical Research Institute provides world class facilities for histology, flow cytometry, Imaging and animal experiments.

About the Clinical Brain Networks:

The Clinical Brain Networks Group focuses on understanding how the structural and functional wiring of the brain underpin health and pathology. The lab uses a variety of neuroimaging, brain stimulation, and computational techniques.

Role Purpose / Responsibilities:

The Clinical Brain Networks Team, led by Associate Professor Luca Cocchi at QIMR Berghofer Medical Research Institute, is seeking a Postdoctoral Research Officer. The role is a key part of an NHMRC-funded project to model large-scale brain dynamics underpinning symptoms of obsessive-compulsive disorder (OCD).

The successful candidate will develop novel models of large-scale brain dynamics, and use these to uncover brain activity causing OCD. This will entail: (i) mathematical and computational modelling of brain dynamics at the whole-brain level; (ii) constraining models against empirical neuroimaging data, both structural and functional; and (iii) developing novel analysis tools and implementing them for wide adoption.

The role will also include collaboration with Dr Paula Sanz-Leon, A/Prof. James Roberts, A/Prof. Andrew Zalesky and Prof. Leonardo Fontenelle.

The following duties will apply:

  • Developing innovative models of large-scale brain activity;
  • Analysing brain structural and activity data, including pre-processing of neuroimaging data;
  • Developing novel analysis methods and implementing them in code for wider adoption;
  • Liaising with external collaborators;
  • Working independently and driving project outcomes with the initiative expected from an experienced graduate;
  • Preparing manuscripts for publication;
  • Participating in intra-mural group activities, including presentation at lab meetings and collaboration with other lab members;
  • Ensuring work practices comply with the requirements of the Work Health and Safety Act, related legislative requirements and the Institute’s WH&S policies and procedures.

About you:

Essential (Qualifications, Experience, Skills, Abilities and Personnel Qualities)

  • PhD in physics, mathematics, computational neuroscience, computer science, or a related field;
  • Strong track record of high-quality peer-reviewed publications;
  • Experience in mathematical modelling;
  • Proficiency in programming (MATLAB and Python);


  • Experience in the pre-processing and analysis of neuroimaging data, including diffusion imaging and fMRI;
  • Experience in modelling large-scale brain network dynamics;
  • Experience in time series analysis and signal processing methods;
  • Experience in collating, handling, and storing large and diverse datasets.


Remuneration: Salary range is $82,506 to $88,522 p.a. plus super and salary packaging. This is a three year, full-time appointment with possible extension.

To submit an application: use the APPLY button. All applicants must supply the following documents: letter of intent, curriculum vitae, list of publications.

For further information: 
Contact Luca Cocchi, Team Head, Clinical Brain Networks; via email

Closing Date:  14 March 2021

What we offer:

  • Salary Packaging
  • Bonus Superannuation
  • State of the art facilities
  • Stimulating work setting focussed on cutting edge medical research
  • Supportive/collaborative team environment
Job Ref: JM000032
Applications Close: Sunday, 14 Mar 2021

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