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PhD in Developing Novel Information Decoding and Tracking Methods to Study Brain and Cognition

  • Australia
  • Posted 4 months ago
  • Applications have closed

University of Queensland

Deadline: May 1, 2024

Project description

The Brain is one of the most complicated information processing systems known. However, we have not yet fully discovered how the brain processes information and solves complicated cognitive problems. This project is aimed at enhancing state-of-the-art methodologies in neural data analysis. While great progress has been made in the past decades on developing methods for neural data analysis, the development of knowledge now allows us to develop methods which can provide unprecedented insights into the brain. This project works on two aspects of neural information processing including how neural activations reflect meaningful information and how those activations transfer information from one area of the brain to another indifferent tasks.

This project involves programming in different programming languages including PYTHON and MATLAB and analysing different modalities of neural data including electroencephalography (EEG), magnetoencephalography (MEG), functional Magnetic Resonance Imaging (fMRI), neurophysiology data and calcium imaging. These datasets will be collected either in the lab by the PhD student and/or obtained from publicly available sources. The project also uses stimulation devices such as Transcranial Magnetic Stimulation (TMS) to evaluate causal role of interference on human cognition.

Research environment

The project is hosted by Queensland Brain Institute (QBI) at the University of Queensland. QBI is home to 250 researchers, all working to unlock the mysteries of the brain to generate new knowledge, understand learning and memory, develop new technologies to improve lives, and diagnose and treat brain disease and mental health.

The project will benefit from using in-house EEG and TMS and on-campus fMRI systems. There is cluster computing facility for high-performance computing available on campus

Scholarship

This is an Earmarked scholarship project that aligns with a recently awarded Australian Government grant.

The scholarship includes:

  • living stipend of $33,641 per annum tax free (2024 rate), indexed annually
  • your tuition fees covered
  • single overseas student health cover (OSHC).

Learn more about the Earmarked scholarship.

Supervisor

You must contact the principal supervisor for this project to discuss your interest. You should only complete the online application after you have reached agreement on supervision.

Always make sure you are approaching your potential supervisor in a professional way. We have provided some guidelines for you on how to contact a supervisor.

Preferred educational background

Your application will be assessed on a competitive basis taking into account your:

  • academic record
  • publication record
  • honours and awards
  • employment history.

Working knowledge of Computer Programming, Machine Learning and Signal Processing would be beneficial.

You’ll demonstrate academic achievement in Computational Neuroscience, Electrical/Biomedical Engineering, Computer Science and the potential for scholastic success.

A background or knowledge of Neural data analysis, Electroencephalography (EEG) is highly desirable.

How to apply

This project requires candidates to commence no later than Research Quarter 4, 2024. To allow time for your application to be processed, we recommend applying no later than 1 May, 2024.

You can start in an earlier research quarter. See application dates.

Before you apply

  1. Check your eligibility for the Doctor of Philosophy (PhD).
  2. Prepare your documentation.
  3. Contact Dr Hamid Karimi-Rouzbahani (uqhkarim@uq.edu.au) to discuss your interest and suitability.

When you apply

You apply for this scholarship when you submit an application for a PhD. You don’t need to submit a separate scholarship application.

In your application ensure that under the ‘Scholarships and collaborative study’ section you select:

  • My higher degree is not collaborative
  • I am applying for, or have been awarded a scholarship or sponsorship
  • UQ Earmarked Scholarship type.

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