PhD Scholarship in Computational and Systems Neuroscience

Monash University


PhD Scholarship - Computational & Systems Neuroscience Laboratory

Job No.: 615267

Location: Clayton campus

Employment Type: Full-time

Duration: 3-year fixed-term appointment

Remuneration: The successful applicant will receive a tax-free stipend, at current value of $29,000 per annum 2020 full-time rate, as per the Monash Research Training Program (RTP) Stipend

Everyone needs a platform to launch a satisfying career. At Monash, we give you space and support to take your career in all kinds of exciting new directions. In this role, you’ll have access to quality research, infrastructure and learning facilities, in addition to opportunities for national and international collaborations. We’re a university full of energetic and enthusiastic minds, driven to challenge what’s expected, expand what we know, and learn from other inspiring, empowering thinkers.

  • Be inspired, every day
  • Drive your own learning at one of the world’s top 70 universities
  • Take your career in exciting, rewarding directions

The Opportunity:

This exciting new PhD position will generate research relevant to the development of brain connectivity analysis methods, with a focus on Network Neuroscience, Machine Learning, Bayesian Inference, and Dynamic Causal Modelling (DCM) – which is a framework for modelling neural circuitry (i.e. effective connectivity).

The “Computational and Systems Neuroscience Laboratory” is headed by Associate Professor Adeel Razi. Our Lab is part of the “Brain Mapping and Modelling” Research Program of the Turner Institute of Brain and Mental Health. Our research vision is to perform cross-disciplinary research combining engineering, physics, and machine-learning approaches to answer questions that are motivated by and grounded in neurobiology. This will enable us to go beyond the traditional boundaries in order to understand how does the brain implement cognition. Our research program’s priority areas include:

  • Development of multi-modal (e.g. functional mri, diffusion mri, eeg) and multi-scale brain connectivity models and methods to characterise brain network dynamics;
  • Development of neuroscience-inspired artificial intelligence schemes to understand how brain performs reasoning, learning and planning;
  • Use of classical psychedelics (e.g. Lsd and psilocybin) in combination with computational modelling to understand neural mechanisms underlying altered states of consciousness.

Further details about our research program and peer-reviewed work is available from:

We are seeking a highly motivated candidate with a Bachelor’s (honours) or Master’s degree in Engineering, Mathematics, Physics, Computer Science, Quantitative Psychology and, ideally, with interest or previous expertise in either Neuroscience, Biomedical Engineering, or closely related field relevant to functional MRI. We particularly encourage applications by candidates with programming ability in either MATLAB, Python or R, and strong quantitative background.

You will be part of an interdisciplinary team of researchers and carry out original research as part of an Australian Research Council (ARC) Discovery Project awarded to Monash University (Dr Adeel Razi, Lead Investigator), University of Melbourne (Associate Professor Andrew Zalesky) and University College London (Professor Karl Friston). The successful applicant(s) will work under the supervision of Associate Professor Adeel Razi and the co-supervision of Dr Leonardo Novelli and will be located at the Monash Biomedical Imaging (MBI), Clayton Campus. Monash Biomedical Imaging is also the home to the ARC Centre of Excellence in Integrative Brain Function. The candidate will also have an opportunity to spend time in our international collaborators’ labs, and there is generous funding available to attend/present at conferences every year. The University will also provide full access to facilities, shared office space, and a laptop computer.

The ideal start date is April 2021 or as soon as possible thereafter.

Knowledge and Skills

  • Excellent written communication and verbal communication skills, with proven ability to produce clear, succinct reports and documents.
  • Programming ability in either MATLAB, Python or R, ideally with experience in handling large datasets.
  • Statistical/mathematical knowledge, ideally with some knowledge of Bayesian modelling techniques.
  • Well-developed organisational and record keeping skills, with the ability to prioritise multiple tasks and set and meet deadlines.
  • Demonstrated strong report and publication preparation skills, ideally with a track record of research resultant in publications, conference papers, reports or professional or technical contributions.
  • Demonstrated computer literacy and proficiency in the production of high-level work using software such as Microsoft Office applications and specified university software programs, with the capability and willingness to learn new packages as appropriate.
  • A demonstrated capacity to work in a collegiate manner with other staff in the workplace as well as the ability to work in a research environment (with supervision).

If this sounds like a position that suits your current career focus, we look forward to hearing from you.

At Monash University, we are committed to being a Child Safe organisation. Some positions at the University will require the incumbent to hold a valid Working with Children Check. 

How to apply

For general instructions on how to apply for roles at Monash, please refer to "How to apply for Monash Jobs".


Associate Professor Adeel Razi, Email:, Phone: + 61 3 9905 0109

Closing Date

Monday 15 March 2021, 11:55pm AEDT

In your application, please refer to


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