Postdoctoral Research Fellow Machine Learning
Computational Intelligence & Brain Computer Interface (CIBCI) Centre, School of Computer Science
At UTS, the concepts of equity and social justice are key to our core and purpose – we are recognised widely as supporting inclusivity and valuing diversity. Cited as a WGEA Employer of Choice since the inception of the award, we are now among the first Australian institutions to receive the Athena SWAN Bronze Accreditation for our commitment to action addressing gender equity in the STEMM disciplines. UTS Equal Futures celebrates and supports women in academia through every stage of their career.
As part of Athena SWAN, UTS has set an overarching target of 40 per cent academic women in STEMM by 2022. The School of Computer Science is committed to UTS’s target and supporting the career development of women academics.
The UTS: Computational Intelligence and Brain Computer Interface Centre is developing mobile sensing technology to measure brain activity using non-invasive methods. We read brain and other physiological signals to assess human cognitive states. Our main research goal focuses on translational neuroscience and machine intelligent systems, including algorithm development and brain-computer interface design.
We are seeking to recruit a Postdoctoral Research Fellow to work closely with the Centre Director, Professor Chin-Teng Lin, on the academic activities associated with CIBCI in Machine Learning.
About the role
The projects main focus is on reinforcement learning algorithms. You will work on designing different hierarchical reinforcement learning architectures. You will have the opportunity to produce publications and deliver presentations and to continue developing your own scholarly standing. You will also provide training to other researchers in technologies and best practices, in addition to training in emerging industry trends of relevance to the centre.
We are looking for a Postdoctoral Fellow who has extensive hands on experience in machine learning algorithms, such as reinforcement learning, deep neural networks, and statistical machine learning analysis. You will have excellent communication skills and the ability to translate and demonstrate academic research results to the general public.
You will also have:
- An ability to identify problem and develop solutions for Human-machine autonomy through physiological signals from human
- An ability to undertake empirical research and a successful record of research achievement including refereed publications and conference presentations
- Demonstrated ability to forge links with the Computational Intelligence profession and other key stakeholders
- A recent doctorate in an appropriate area of computer science.
Remuneration & Benefits
Base Salary Range: $103,981 to $ $123,067 pa (Level B)
This role attracts 17% superannuation (pension) in addition to the base salary.
UTS staff also benefit from a wide range of Employee Benefits include flexible work practices, child care centres, generous parental leave and salary packaging opportunities.
This positions are full-time and appointment will be made on a fixed term basis for three years.
How To Apply
For the full list of the selection criteria and role responsibilities please click apply and download the Position Statement from the UTS website.
UTS is committed to diversity and inclusion in our workforce and we encourage applicants, where relevant, to include a relative to opportunity or career disruption/break statement within their CV.
You are required to address the selection criteria in your submission in a separate document.
Only those applications submitted via the UTS online recruitment system will be accepted. Current UTS employees should apply through their UTS Employee Self Service function.
As you will be unable to save your application once started, please have all required documents and information available prior to commencing.
Please ensure that the file name for each document submitted includes IRC132856.
Specific enquiries or issues with your application may be directed to the UTS Recruitment Team at email@example.com or on +61 (0) 2 9514 1080.
Please be advised that as part of the selection process that you may be requested to deliver a presentation, the audience for which may include individuals not on the Selection Panel.
Closing Date: Monday June 10th 2019 at 11.59pm (AEST)
Please note: If you have a disability that requires adjustment to the recruitment process or an alternative application pathway please contact firstname.lastname@example.org for assistance.
We welcome applications from women, Indigenous Australians, people with disability, those who identify as LGBTIQ and applicants from culturally and linguistically diverse backgrounds.