Research Associate/Senior Research Associate in Optimisation and Reinforcement Learning

The Opportunity

The School of Computer Science and Engineering has an opportunity for a Research Associate/Senior Research Associate. In this role you will carry out independent and team research and activities to develop your research expertise relevant to the field of optimisation and reinforcement learning. The R&D will be focused towards developing an AI Gym platform, a benchmark and experiment sandbox for orchestrating flexible demand assets in an electricity market. The research will be conducted as a part of an international collaboration network – Mission Innovation 2.0, with participants from more than 14 countries, towards the ongoing energy transition efforts, led by CSIRO (https://research.csiro.au/dch/projects/icirn/). This work will help towards addressing this global challenge.

This position will give you the opportunity to develop your scholarly research and professional activities both nationally and internationally through your contributions to the writing of scientific papers and reports for international journals, your participation in conferences and workshops, and your active engagement with industry partners.

This role reports to Professor Flora Salim and has no direct reports.

• Salary
  • Level A, Research Associate - AUD$110,059 to $117,718 per annum + 17% superannuation
  • Level B, Senior Research Associate – AUD$123,620 per annum + 17% superannuation
• Full time
• Fixed-term contract – 1.5 to 2 years
• Location: Kensington – Sydney, Australia

About UNSW

UNSW isn’t like other places you’ve worked. Yes, we’re a large organisation with a diverse and talented community; a community doing extraordinary things. But what makes us different isn’t only what we do, it’s how we do it. Together, we are driven to be thoughtful, practical, and purposeful in all we do. If you want a career where you can thrive, be challenged and do meaningful work, you’re in the right place.

The School of Computer Science and Engineering is one of the largest and most prestigious schools of computing in Australia. It offers undergraduate programmes in Software Engineering, Computer Engineering, Computer Science, and Bioinformatics, as well as a number of combined degrees with other disciplines. Our research and teaching staff are world leading and world building as they advance knowledge and learning. For more information on our school go to the following link - https://www.unsw.edu.au/engineering/our-schools/computer-science-and-engineering

Skills and Experience

Level A - Research Associate

• A PhD (or soon to be awarded) in a related discipline, and/or relevant work experience.
• Demonstrated track record in research, evidenced by publications in top-tier AI and ML conferences, such as NeurIPS, AAAI, IJCAI, ICLR, ICML, CVPR, with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research excellence as well as the capacity for research leadership.
• Strong experience in at least two of the following areas:
• reinforcement learning
• machine learning, deep learning
• dynamic scheduling, optimisation and control
• Experience in developing comprehensive benchmarks
• Robust coding and software engineering skills
• Experience in participating in or running a datathon or machine learning competition is preferred, but not required
• Experience in handling time-series data, specifically energy, sensors and IoT data, is required
• Proven commitment to proactively keeping up to date with discipline knowledge and developments
• Demonstrated ability to undertake high quality academic research and conduct independent research with limited supervision.
• Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.

Level B – Senior Research Associate

• A PhD in a related discipline, and/or relevant work experience.
• Demonstrated track record in research, evidenced by publications in top-tier AI and ML conferences, such as NeurIPS, AAAI, IJCAI, ICLR, ICML, CVPR, with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research excellence as well as the capacity for research leadership.
• Strong experience in all the following areas:
• reinforcement learning
• machine learning, deep learning
• dynamic scheduling and control
• Experience in developing comprehensive benchmarks
• Robust coding and software engineering skills
• Experience in participating in or running a datathon or machine learning competition is preferred, but not required
• Experience in handling time-series data, specifically energy, sensors and IoT data, is required
• Proven commitment to proactively keeping up to date with discipline knowledge and developments.
• A track record of significant involvement with the profession and/or industry.
• A strong practice of maintaining open-source code repository.
• High level communication skills and ability to network effectively and interact with a diverse range of students and staff.
• Ability to build effective networks with colleagues and generate alternative funding and/or industry projects through effective liaison with external local and international researchers, industry and government.

Additional details about the specific responsibilities for this position can be found in the position description. This is available via JOBS@UNSW.

To Apply:

Please click the apply now button and submit your CV, Cover Letter and Responses to the Skills and Experience. You should systematically address the Skills and Experience listed within the position description in your application.

Please note applications will not be accepted if sent to the contact listed below.

Contact:

Eugene Aves – Talent Acquisition Consultant

E: [email protected]

Applications close: 11:55 pm (Sydney time) on Sunday 7^th July 2024

UNSW is committed to evolving a culture that embraces equity and supports a diverse and inclusive community where everyone can participate fairly, in a safe and respectful environment. We welcome candidates from all backgrounds and encourage applications from people of diverse gender, sexual orientation, cultural and linguistic backgrounds, Aboriginal and Torres Strait Islander background, people with disability and those with caring and family responsibilities. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.