Senior Lecturer / Associate Professor in Fairness in Machine Learning and AI Planning
Role type: Full time; Continuing
Faculty: Faculty of Engineering and Information Technology
Department/School: School of Computing and Information Systems
Salary: Level C – $135,032 – $155,698 or Level D – $162,590 – $179,123 p.a. plus 17% super
- Opportunity to demonstrate your leadership and make a valuable contribution to teaching and research in the discipline of Machine Learning
- Join a world-class computer science research group and collaborate with internationally respected groups across AI, HCI and IS
- Further develop your academic and leadership profile and be supported to achieve your goals across all pillars of an academic career
The University of Melbourne would like to acknowledge and pay respect to the Traditional Owners of the lands upon which our campuses are situated, the Wurundjeri and Boon Wurrung Peoples, the Yorta Yorta Nation, the Dja Dja Wurrung People. We acknowledge that the land on which we meet and learn was the place of age-old ceremonies, of celebration, initiation and renewal, and that the local Aboriginal Peoples have had and continue to have a unique role in the life of these lands.
About the School of Computing and Information Systems (CIS)
We are international research leaders with a focus on delivering impact and making a real difference in three key areas: data and knowledge, platforms and systems, and people and organisations.
At the School of Computing and Information Systems, you'll find curious people, big problems, and plenty of chances to create a real difference in the world.
To find out more about CIS, visit: http://www.cis.unimelb.edu.au/
About the Role
The Faculty of Engineering and Information Technology (FEIT) is seeking an aspiring academic leader with expertise in algorithms and their fairness in machine learning and/or AI (artificial intelligence) planning, or related fields, for a substantive position within the School of Computing and Information Systems (CIS).
You will join a world-class computer science research group, which has strong links to the Centre for AI & Digital Ethics (CAIDE) and will be expected to collaborate with both alongside other internationally respected groups across artificial intelligence, human-computer interaction, information systems.
You highly ambitious and eager to demonstrate world leading research through publications in key conferences (typified by, but not limited to, FAccT, The Web Conference, KDD, NeurIPS, ICAPS, AAAI, IJACI, ITCS, EC, CHI, CSCW) and in high-quality journals (typified by, but not limited to, ACM TKDD, AIJ, ACM Transactions on Economics and Computation, Proceedings of the National Academy of Sciences, Big Data and Society, AI and Society, AI and Ethics, TCS). You will make a valuable contribution to the School and broader academic community through mentorship, contributions to teaching into various Masters programs related to algorithms, theory, digital ethics and related areas and provide critical leadership in engagement activities including securing grant funding to support your program of research.
This is an exciting opportunity to further develop your academic and leadership profile and be supported to achieve your goals across all pillars of an academic career.
- Providing a significant degree of scholarly research initiative and collaboration in the discipline of machine learning, exercising leadership over projects, securing funding and publishing in top-tier conferences and journals.
- Fostering an excellent teaching experience for our students including coordinating and conducting lectures and tutorials at undergraduate and postgraduate level and engagement in continuous teaching innovation and improvement.
- Supervising undergraduate, graduate or postgraduate students engaged in coursework or smaller research projects
- Leading and optimising partnerships with industry, government, collaborators at other Universities and other stakeholders consistent with the School’s strategic plan.
You are an aspiring leader with the ability to build a highly respected reputation in Machine Learning and/or AI Planning, as demonstrated through a significant track record of publications in high-impact peer-reviewed and refereed venues, and invitations to speak at national and international meetings. You are experienced in mentoring both students, colleagues and research teams and demonstrate great initiative in the establishment and nurturing of research projects. Your highly-developed communication and relationship building skills enable you to engage with a diverse range of people and institutions to develop partnerships that positively contribute to strategic initiatives.
You will also have:
- A PhD in computer science or another discipline relevant to Algorithmic Fairness in Machine Learning and/or AI Planning.
- Evidence of leadership of a research team, with demonstrated ability to manage collaborative projects and research activities, involving the management of personnel, timelines and budgets, and relationships with various stakeholders.
- Experience in curriculum development and implementation at undergraduate and postgraduate level that will maintain the School’s programmes at the highest international standards.
- Capacity to teach effectively and develop educational programs and methods across a range of subjects, in particular in the field of algorithmic fairness in machine learning and/or AI planning.
- Capacity to develop an international funding profile.
For full details of responsibilities and selection criteria, including criteria for a Level D appointment, please refer to the attached position description.
To ensure the University continues to provide a safe environment for everyone, this position requires the incumbent to hold a current and valid Working with Children Check.
About - The Faculty of Engineering and Information Technology (FEIT)
The Faculty of Engineering and Information Technology (FEIT) has been the leading Australian provider of engineering and IT education and research for over 150 years. We are a multidisciplinary School organised into three key areas; Computing and Information Systems (CIS), Chemical and Biomedical Engineering (CBE) and Electrical, Mechanical and Infrastructure Engineering (EMI). FEIT continues to attract top staff and students with a global reputation and has a commitment to knowledge for the betterment of society.
About the University
The University of Melbourne is consistently ranked amongst the leading universities in the world. We are proud of our people, our commitment to research and teaching excellence, and our global engagement.
Benefits of Working with Us
In addition to having the opportunity to grow and be challenged, and to be part of a vibrant campus life, our people enjoy a range of rewarding benefits:
- Flexible working arrangements, generous personal, parental and cultural leave
- Competitive remuneration, 17% super, salary packaging and leave loading
- Free and subsidised health and wellbeing services, and access to fitness and cultural clubs
- Discounts on a wide range of products and services including Myki cards and Qantas Club
- Career development opportunities and 25% off graduate courses for staff and their immediate families
To find out more, visit https://about.unimelb.edu.au/careers/staff-benefits.
We value the unique backgrounds, experiences and contributions that each person brings to our community and encourage and celebrate diversity. First Nations people, those identifying as LGBTQIA+, females, people of all ages, with disabilities and culturally and linguistically diverse people are encouraged to apply. Our aim is to create a workforce that reflects the community in which we live.
If you feel this role is right for you, please apply with your CV and cover letter outlining your interest and experience. Please note that you are not required to provide responses against the selection criteria in the Position Description.
We are dedicated to ensuring barrier free and inclusive practices to recruit the most talented candidates. If you require any reasonable adjustments with the recruitment process, please contact us at email@example.com.
Position Description: 0054173_PD_C D in Fairness.pdf
Applications close: Monday 26 September 2022 11:55 PM AUS Eastern Standard Time