Lecturer In Machine Learning In Business

Lecturer in Machine Learning in BusinessApply
Location: Darlington Campus
Time Type: Full time
Posted on: Posted 11 Days Ago
Job Requisition ID: 0119443
Full time continuing (tenure-track) academic Lecturer Teaching and Research positions (equivalent to Assistant Professor) at The University of Sydney with a potential for an introductory teaching load reductionIntellectually stimulating and rewarding work environment in an ambitious team housed in a modern world-class facilityBase Salary Level B AUD$122,830 p.a. – AUD $145,858 p.a., with potential for a market loading, + 17% superannuation, 36-week paid parental leave and other generous benefitsSubstantial research start-up package and access to continued research supportAbout the opportunity The University of Sydney welcomes applications for various academic disciplines outlined below, during an exciting and innovative time. With the introduction of the new University of Sydney Enterprise Agreement 2023-26, the University has committed to establishing and advertising new continuing teaching and research academic positions across the University of Sydney Business School.
You will have the opportunity to make a significant contribution to teaching in your field of expertise while you also continue to build substantial research contribution, expertise, connections, and impact. As part of this role, you will also contribute to the governance, leadership, and engagement work of your employing school.
Over time, staff appointed to these roles will be supported to engage with professional development opportunities to build their capability to lead change and improvement in teaching and research at the University. The University of Sydney is recognised as one of the top research and teaching universities in the world. A globally ranked university, ranked 18th in QS University World Rankings 2025, 1st for sustainability in Australia.
The University of Sydney Business School is one of the Asia Pacific region's premier centers for engaged and innovative business education and research, and is in the one percent of business schools globally to hold accreditation from AACSB, EQUIS and AMBA.
The Discipline of Business Analytics is a group of scholars working in the intersection of such quantitative fields as Econometrics and Statistics, Computer Science and Machine Learning, and Operations Research and Operations Management. We are engaged in all aspects of analysing data and building predictive and causal models to assist in business decision-making. The Discipline has research strengths in such areas as Bayesian and computational statistics, business and economic forecasting, financial and nonparametric econometrics, high-dimensional statistics, mathematical optimisation, quantitative risk management, scheduling theory, statistical machine learning, and supply chain management.
Teaching and Research Opportunities The aims of these teaching and research roles are to attract and retain the best and brightest emerging academics. To support an uplift in the teaching and research capability and student experience at the University of Sydney, these positions are for talented researchers who also have a passion for, and demonstrated excellence in, pedagogical practice.
Successful candidates are expected to allocate their contributions as follows: 40% to teaching and related activities, 40% to research, and 20% to governance, leadership, and engagement.
Your key responsibilities will be to:
Contribute to existing and emerging research strengths of the School, including regular publication in journals of high standing within your discipline or area of expertise, pursuing research grants, and presenting and disseminating research findings through appropriate channels.Design and engage in cutting-edge, innovative and high-quality teaching and learning at the undergraduate and postgraduate level to large and culturally diverse student cohorts, according to the University's expectations and standards for education, delivering outstanding teaching and learning outcomes for students.Be involved in interdisciplinary collaborations within the University and with external partners.Contribute to academic governance, leadership, and engagement work in your school.Supervise research students.Maintain relevant Work, Health and Safety requirements.Develop and refine your research skills.About you The University values trust, accountability and excellence. As such, we see the importance of recruiting talented academics who align to these values and who will lead our teaching and research work at the university in the years to come. You will join a dynamic, engaged group in a highly collaborative and supportive teaching and research environment.
We are looking for candidates who can make a significant contribution to teaching and learning design, delivery, and evaluation while continuing to build their research contribution, expertise and impact. They will have a demonstrated ability to interact effectively with students, facilitating and guiding their learning in research, theory and laboratory sessions. They will also have the capacity to build a significant research program over time, obtaining competitive funding as needed to support their research work.
We are therefore looking for Teaching and Research Appointments who have:
A PhD or nearly completed PhD in Computer Science, Machine Learning, or a related field.An active research program with significant potential for future publications in the field of specialisation.Evidence of high-quality teaching potential in the field of specialisation and interest in or potential for teaching in interdisciplinary teams.Demonstrated capacity to stimulate, actively engage and educate a range of audiences using various media.Capacity to contribute to curriculum development.Potential for engagement and collaboration with partners from industry and government.Evidence of successful teamwork and a collegial approach.Pre-employment checks Your employment is conditional upon the completion of all role-required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements.
How to apply Please prepare and upload your application, including a cover letter that indicates how you believe you meet the criteria outlined above in the "About you" of the advertisement (maximum 3 A4 pages), CV, job market paper, student evaluations (if available) and contact information for three letters of reference, and any additional supporting documentation via the Apply button at the top of the page.
Contact Information For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Justyn Griffin, Recruitment Partner. Recruitment Operations, Human Resources by email ******.
Applications Close Monday 16 December 2024 11:59 PM
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