Post-doctoral Research Fellow (A/B) in Machine Learning

Employer
The University of Adelaide
Location
Adelaide, Australia
Salary
$71,401 to $119,391 per annum including an employer contribution of up to 17% superannuation may app
Closing date
May 22, 2022

View more

Sector
Science, Computer Science and IT, Computer Science, Chemistry, Chemical Engineering, Mathematics and Statistics
Hours
Full Time
Organization Type
University and College
Jobseeker Type
Academic (e.g. 'Lecturer')
We are seeking to appoint a Post-doctoral Research Fellow (Level A/B) in Machine Learning - A 1.5 year fixed-term position is available to work on a research project for developing Machine Learning methods for network protocol evaluation with the possibility of extension to 3 years.

This is a fantastic opportunity for a high-achieving postdoctoral researcher to join a world-leading research group in Computer Security and Machine Learning as well as Computer Science department ranked 48th in the world and The University of Adelaide ranked in the top 1% of Universities worldwide.

You will work on a research program to address the problems in software-based emulation and assessment of networking protocols to support automated dynamic analysis of networking protocols.

The project aims to develop and implement methods to automatically find vulnerabilities and attack strategies in common Internet routing protocols. You will be involved in the development of theory, techniques (such as fuzzing and machine learning methods) and tools for discovering bugs and vulnerabilities in protocol implementations.

You will work with a team of researchers from the University of Adelaide's School of Computer Science and the Australian Institute of Machine Learning, University of New South Wales, CSIRO's Data61 and Defence Science and Technology Organisation (DSTG).

In this role you will have the options to purse one or more of the following:
  • Investigate and develop machine learning techniques and/or optimisation methods for intelligent generation of structured text inputs.
  • Develop unsupervised, semi-supervised, and reinforcement learning techniques for Context-sensitive and context-free grammar.
  • Investigate domain adaptation methods in the discrete data generation fields such as text, code and binary data.
  • Develop machine learning methods for automata learning.

This is an outstanding opportunity to advance your career in cyber security, network security, computer security, software engineering and machine learning whilst exploring the area of large scale, automated, dynamic analysis of networking software with three world-class institutions in a world-leading environment.

The University of Adelaide is a member of Australia's prestigious Group of Eight research-intensive universities and ranks inside the world's top 100. In the Australian Government's 2018 Excellence in Research for Australia (ERA) assessment, 100% of University of Adelaide research was rated world-class or above, with work in 41 distinct fields achieving the highest possible rating of 'well above world-standard'. This included Artificial Intelligence and Image Processing, and Electrical and Electronic Engineering.

Our world-renowned researchers have established a culture of innovation and a strong track record of publication in the top venues, particularly in the area of machine learning, computer vision and security. We're committed to delivering fundamental and commercially oriented research that's highly valued by our local and global communities. Here you'll work in one of the world's most talented and creative machine learning teams, with constant research-engineering collaboration. You'll use state-of-the-art technology and you'll be based in the heart of one of the world's top 10 most liveable cities.

To be successful you will need

Level A
  • PhD (or soon to be awarded) in Computer Science or Software Engineering or a similar discipline OR equivalent industry experience in software development, computer networking protocols, applied machine learning, computer security.
  • Experience and demonstrable expert knowledge in one or more of the following areas:
    • Machine learning in general (example areas include Natural Language Processing, Text Classification, Graph Neural Networks, Convolutional Neural Networks, Generative Adversarial Networks, Sequence Learning algorithms, Transformers).
    • Machine learning domain expertise working with binaries, text, structured data, sequential data or time series data and discrete data.
    • Optimisation techniques (applications in software engineering).
  • Programming experience and expertise in Rust/C/C++/Python and expertise in one or more deep learning tools such as: PyTorch, TensorFlow
  • Fluency in written and spoken English, with an ability to communicate scientific ideas to an expert audience
  • Commitment to the principles of equity, diversity and inclusion

Level B (in addition to the above)
  • Extensive programming experience and expertise in Rust/C/C++/Python and expertise in one or more deep learning tools such as: PyTorch, TensorFlow
  • A strong track record of publications and/or developing software products & tools commensurate with experience and opportunity.
  • Demonstrated ability to conduct independent research and development with limited supervision.

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 Sciences, Engineering and Technology is a multidisciplinary hub of cutting-edge teaching and research. Many of its academic staff are world leaders in their fields and graduates are highly regarded by employers. The Faculty actively partners with innovative industries to solve problems of global significance.

Learn more at: set.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, 12 June 2022.

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 selection criteria via the link 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.

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