Researcher in Machine Learning and Security

University of Adelaide School of Computer Science

Australia

Grant Funded Researcher (A/B/C) in Machine Learning and Security

Job no: 506112
Work type: Fixed term - Full-time
Campus: Adelaide
Categories: Faculty of Engineering, Computer & Mathematical Sciences, Level A, Level B, Level C

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(Level A) $89,610 to $96,007 or (Level B) $100,933 to $119,391 or (Level C) $123,075 per annum plus an employer contribution of up to 17% superannuation may apply. 

Two, 1.5 year fixed-term positions are available to work on a project for Robustness and Security in Machine Learning (with possibility of extension to 3 years).

This is an outstanding opportunity to advance your machine learning and artificial intelligence knowledge and career, and explore the emerging area of machine learning security with two world-class institutions in a world-leading environment.

This opportunity is for a high-achieving postdoctoral researcher to join a world-leading research group in Computer Security and Machine Learning. The School of Computer Science is ranked 48th in the world and The University of Adelaide ranked in the top 1% of Universities worldwide. Notably, Adelaide is ranked the third most liveable city in the world, and the most liveable city in Australia in 2021.

As a Grant Funded researcher, you will work on a research program to improve the trustworthiness of systems integrating machine learning models and promote secure designs. This project aims to develop theory, techniques, and tools for building more robust and resilient machine learning systems. You will work with a team of researchers from the University of Adelaide’s School of Computer Science and the Australian Institute for Machine Learning, University of New South Wales, CSIRO’s Data61 and Defence Science and Technology Organisation (DSTG).

In this role you will investigate and develop new ideas and concepts for defending against adversarial and data poisoning attacks, formulate solutions, implement, and assess the robustness of the methods against attacks. As well as developing theoretical aspects of machine learning.

To be successful at Level A you will need:

  • PhD (or soon to be awarded) in Computer Science or a similar discipline, or equivalent industry experience.
  • Experience and demonstrable expert knowledge in one or more or the following areas: Bayesian learning; Adversarial machine learning; Machine learning security and privacy; Graph neural networks; Multi-modal learning and representation; Generative adversarial networks; Transformers; Domain generalisation; Deep learning in general; machine learning domain expertise working with text, software, networks, malware, sequential data or time series data and discrete data.
  • Programming experience and expertise in Python, or C++.
  • Expertise in one or more deep learning tools such as: PyTorch, TensorFlow, Caffe, Keras.
  • Track record of publications in leading conferences and/or journals in Computer Vision, Machine Learning, Artificial Intelligence, Optimisation, Computer Security, commensurate with experience and opportunity.

In addition to the above to be successful at Level B, you will also need:

  • A strong work ethic and the ability to work well independently, and as a member of a broader team, including with industrial partners
  • A strong track record of generating new ideas and quality research as evidenced by publications in one or more of top-tier machine learning, artificial intelligence, computer security conferences and/or journals commensurate with experience and opportunity.

In addition to the above to be successful at Level C, you will also need:

  • Post-doctoral research experience (industry and/or academia).
  • A strong track record of building new research directions and leading quality research programs in the area of machine learning, artificial intelligence and/or computer security evidenced by one or more of: investigator roles in grants, contract research, consultancies, media stories, joint publications with project partners, patents, commercialisations or other non-commercial outcomes.

Enjoy an outstanding career environment

The University of Adelaide is a uniquely rewarding workplace. The size, breadth and quality of our education and research programs - including significant industry, government and community collaborations - offers you vast scope and opportunity for a long, fulfilling career.

It also enables us to attract high-calibre people in all facets of our operations, ensuring you will be surrounded by talented colleagues, many world-leading. Our work's cutting-edge nature - not just in your own area, but across virtually the full spectrum of human endeavour - provides a constant source of inspiration.

Our culture is one that welcomes all and embraces diversity consistent with our Staff Values and Behaviour Framework and our Values of integrity, respect, collegiality, excellence and discovery. We firmly believe that our people are our most valuable asset, so we work to grow and diversify the skills, knowledge and capability of all our staff.

We embrace flexibility as a key principle to allow our people to manage the changing demands of work, personal and family life. Flexible working arrangements are on offer for all roles at the University.

In addition, we offer a wide range of attractive staff benefits. These include: salary packaging; flexible work arrangements; high-quality professional development programs and activities; and an on-campus health clinic, gym and other fitness facilities.

Learn more at: adelaide.edu.au/jobs

Your faculty's broader role

The Faculty of Engineering, Computer and Mathematical Sciences is a thriving centre of learning, teaching and research in a vast range of engineering disciplines, computer science - including machine learning, high-level mathematics and architecture, planning and landscape architecture. Many of its academic staff are world leaders in their fields and graduates are highly regarded by employers.

Learn more at: ecms.adelaide.edu.au

If you have the talent, we'll give you the opportunity. Together, let's make history.

Click on the ‘Apply Now’ button to be taken through to the online application form. Please ensure you submit a cover letter, resume, and upload a document that includes your responses to all of the selection criteria for the position as contained in the position description or selection criteria document.

Applications close 11:55pm, 3 October 2021.

For further information

For a confidential discussion regarding this position, contact:

Damith Ranasinghe
Associate Professor, School of Computer Science 
P: +61 (8) 8313 0066
E: damith.ranasinghe@adelaide.edu.au

You'll find a full position description and/or selection criteria below: (If no links appear, try viewing on another device)

The University of Adelaide is an Equal Employment Opportunity employer. Women and Aboriginal and Torres Strait Islander people who meet the requirements of this position are strongly encouraged to apply.

Advertised: 03 Sep 2021 12:00 AM
Applications close:03 Oct 2021 11:55 PM


In your application, please refer to Professorpositions.com

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