Work type:Fixed term - Full-time
Categories:Faculty of Engineering, Computer & Mathematical Sciences, Level B
(Level B) $100,933 to $119,391 per annum plus an employer contribution of up to 17% superannuation may apply
2 year fixed-term position available
Work on an ARC linkage project for Machine Learning driven flow modelling of fragmented rocks in cave mining
This is an outstanding opportunity to advance your machine learning; artificial intelligence; and cave mining AI research career with a world-class institution in a world-leading environment.
The research will be hosted at the Australian Institute for Machine Learning, Australia’s premier research institution in artificial intelligence, machine learning and computer vision.
The multipipeline and multi-organisation team consists of A/Prof Murat Karakus (project lead, UoA), A/Prof Giang Nguyen (UoA), Professor Javen Shi (machine learning lead, UoA), Dr Cristiana Ciobanu (UoA), Dr Ha Bui (Monash University), Dr Abbas Taheri (UoA), and Dr Chris Chester (OZ Minerals).
The postdoctoral researcher will be supervised by Professor Javen Shi, and work with domain experts on the machine learning aspect of the project, which includes; developing deep learning methods that take Micro Scale information (such as mineral content distribution) to predict Macro Scale information (such intact rock compressive strength, brittleness and grain size distribution), and then use both to predict Block Scale information (such as rock quality designation, spacing of discontinuities); developing deep learning methods to accelerate or bypass some part of the smoothed particle Hydrodynamics approach (SPH) which is the current state-of-the-art simulation method of block cave mining process; developing a predictive caving chart involving Micro, Macro, and Block Scale information and developing a novel active learning method that can predict which samples to test next (without testing all), and even which/where to drill the hole next (without drilling all), to gain sufficient data for all previous 3 machine learning tasks.
The University’s Australian Institute for Machine Learning (AIML) is Australia’s pre-eminent research institute in machine learning, AI and computer vision. It’s also the country’s largest, with over 130 members, including academics, research staff and students.
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 computer vision. 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
- Have a PhD in Computer Science or related discipline, or equivalent industry experience.
- Programming experience and expertise in Matlab, Python, or C++ or other relevant language.
- Experience and demonstrable expert knowledge in one or more or the following areas; multimodal learning and representation, medical image processing and segmentation, vision-and-language technology including Visual Question Answering, Probabilistic graphical modelling or deep learning in general.
- Track record of publications in top-tier Computer Vision, Artificial Intelligence or Optimisation conferences and/or journals, commensurate with experience and opportunity.
- A strong work ethic, and the ability to work well independently, and as a member of a broader team, including with industrial partners.
To learn more about working at AIML, visit: adelaide.edu.au/aiml/career-opportunities
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 and 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. And 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, 7 October 2021.
For further information
For a confidential discussion regarding this position, contact:
Dr Kathy Nicholson
Australian Institute for Machine Learning
T: +61 (8) 831 39258
M: +61 449 833 241
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.
Download the Position Description Apply now
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