PhD Scholarship: Machine learning in adaptive brain stimulation

St Lucia, Queensland, au
Company: The University of Queensland
Category: Educational Instruction and Library Occupations
Published on 2021-06-12 19:10:12

Research Environment

UQ ranks in the top 50 as measured by the Performance Ranking of Scientific Papers for World Universities. The University also ranks 46 in the QS World University Rankings, 42 in the US News Best Global Universities Rankings, 66 in the Times Higher Education World University Rankings and 54 in the Academic Ranking of World Universities.

The Queensland Brain Institute

The Queensland Brain Institute (QBI) is situated on the St Lucia campus of The University of Queensland. Established as a neuroscience research institute in 2003, its dedicated team of over 400 research staff, including 36 laboratory heads or group leaders, work to understand the development, organisation and function of the healthy and the diseased brain. Their findings are then applied to the development of new therapeutic approaches to prevent and/or restore loss of function in diseases of the nervous system, such as Alzheimer’s and other dementias, stroke, schizophrenia, motor neurone disease, Parkinson’s disease, anxiety and depression.

QBI’s success is evidenced through the number of peer-reviewed high-quality publications that are produced each year, and their success in competitive grant funding schemes, always well-above the national averages.

Over the past decade QBI has played a key role in contributing to UQ attaining the highest possible score of 5 for neuroscience, in the 2010, 2012, 2015 and 2018 Excellence in Research for Australia (ERA) reviews, one of only two universities in Australia to achieve this.

Our people are our greatest asset. We offer collaborative, inclusive work and study places, which are enriched by the significant diversity of our staff, students and community. We genuinely believe that creativity and innovation flourishes in an environment where people feel supported, valued and empowered. Mutual respect, inclusivity and accountability are at the cornerstone of UQ’s culture.

Information about the Institute may be accessed at

Max Kelsen

Max Kelsen (MK) is a Queensland-based artificial intelligence and machine learning company, founded in 2015. In 2020, MK was announced a partner of the year by both Google Cloud (GC) and Amazon Web Services (AWS). It was also ranked 29th by The Deloitte Technology Fast 50 2020 Australia program. In 2021, it ranked 64th overall and 13th in Australia in the Financial Times 2021 list of high-growth companies in APAC. Despite these impressive statistics it is crucial to note that MK is not just another AI consultancy. It stands out from the commercial crowd by building trust and giving back to society through its healthcare focused research. MK research group engages in collaborative projects with world class academics across Australia, Asia and the US. Its aim is to contribute meaningfully to the scientific knowledge and to provide real world AI solutions to a variety of human wellbeing issues, such as COVID, Parkinson’s disease, cancer, heart failure, and glaucoma.

Information about the company may be access at www.maxkelsen.com

The award

Supervisor: Professor Pankaj Sah

This PhD project will use machine learning towards developing adaptive deep brain stimulation, with a focus on application for Parkinson’s disease. Deep brain stimulation is an established therapy for treating movement disorder symptoms and is now being developed to address unmet needs in epilepsy, depression and Alzheimer’s disease. Further personalising the therapy using adaptive techniques will be critical for increasing patient uptake, application to new indications, and improving both the patient experience and clinicians’ workload management.

We are studying the neurophysiology of neurological disorders in humans and animal models to improve clinical outcomes for deep brain stimulation. In this PhD project, you will access large datasets consisting of human and animal brain recordings, behavioural data, and environmental data, and use machine learning towards creating an adaptive deep brain stimulation algorithm.

The candidate will work closely with Queensland artificial intelligence and machine learning company Max Kelsen (www.maxkelsen.com), and be part of an interdisciplinary team of pre-clinical and clinical neuroscientists seeking improved outcomes for patients with movement disorders.

The ideal candidate for this project would:

  • Be proficient in Python programming language for the purpose of data analysis.
  • Have experience with High Performance Computing, ideally with some experience using cloud services, such as Google Cloud
  • Be familiar with multivariate and nonlinear dynamical approaches in analysing time series data (preferably neurophysiological signals)
  • Possess a keen interest and ability to stay informed about the latest, most important developments in AI applications for neuro-engineering
  • Have a demonstrated interest in neuroscience and brain function
  • Have an understanding of deep neural networks and machine learning techniques (preferred but not essential – advanced AI training will be provided through collaboration with Max Kelsen)
  • Have experience in data collection for neurophysiology experiments (preferred but not essential).
  • Selection criteria

    To be eligible to apply, you must also meet the entry requirements for Higher Degrees by Research at UQ. Applications will be judged on a competitive basis taking into account the applicant’s previous academic record, publication record, honours and awards, and employment history.

    The applicant will demonstrate academic achievement in at least one of the following:

  • Physiology
  • Signal processing
  • Machine learning.
  • However, if only one of the fields is demonstrated, the applicant should show convincing evidence of interest in at least one other. For example, a candidate experienced in physiology would need to demonstrate interest in machine learning by having completed basic ML courses. Furthermore, the candidate must demonstrate the potential for scholastic success.

    A first-class honours degree or relevant experience would be highly valued.

    Scholarship

    The 2021 Research Training Program (RTP) living allowance stipend rate is AUD$28,597 per annum (indexed annually), which is tax-free for three years with two possible extensions of up to 6 months each in approved circumstances (conditions apply). Single Overseas

    Enquiries

    For further information, please contact Professor Pankaj Sah at

    How to apply

    To apply for admission and scholarship, follow this link. There is no separate application for scholarship because you will have the opportunity to request scholarship consideration on the application for admission.

    Before submitting an application you should:

  • check your eligibility 
  • prepare your documentation
  • contact Professor Pankaj Sah () to discuss your suitability for this scholarship
  • See an example of what you have to do

    Learn more about applying for a higher degree by research at UQ

    #LI-DNI

    Jobs you might also be interested in