Lecturer in Data Science

Lecturer in Data Science 

• One of Australia’s leading research & teaching universities
• Vibrant campus life with a strong sense of community & inclusion
• Enjoy a career that makes a difference by collaborating & learning from the best 

At UNSW, we pride ourselves on being a workplace where the best people come to do their best work. 

THIS ROLE IS LOCATED IN SYDNEY, AUSTRALIA.

The School of Mathematics and Statistics currently has more than sixty continuing academic staff and more than thirty research staff as well as visiting academics. UNSW is the only university in Australia to be ranked in the top 100 in the world in Mathematics and Statistics by each of the four ranking bodies: CWTS Leiden, ARWU, USNews, QS. The School embodies a broad range of research interests in the areas of applied and pure mathematics and statistics. It has particular research strengths in Algebra and Number Theory, Bayesian and Monte Carlo Methods, Mathematical Modelling and Biomathematics, Biostatistics and Ecology, Combinatorics, Computational Mathematics, Data Science, Dynamical Systems and Integrability, Finance and Risk Analysis, Functional and Harmonic Analysis, Geometry, Mathematical Physics, Nonparametric Statistics, Ocean and Atmospheric Sciences, Optimisation, Stochastic Analysis, Stochastic Modelling and Fractional Calculus. The School's research groups are interconnected, with frequent interactions between groups and with other schools and faculties both within and outside UNSW. The School is currently expanding its teaching and research programs in Data Science. The School is affiliated with the newly established UNSW Data Science Hub which is a major strategic initiative of the Faculty of Science to cultivate and promote foundational and applied research in Data Science.

The Lecturer in Data Science will; (i) conduct research in this specialized field and align, where possible, with the existing research strengths in the School; (ii) contribute actively to the School’s teaching activities in Data Science and Statistics across a range of undergraduate and postgraduate courses, including online teaching; (iii) engage with the community and industry to build links in Data Science.

Women and candidates from diverse backgrounds are particularly encouraged to apply. 

About the role

• $109k - $128k - plus 17% Superannuation and leave loading
• Fixed Term – 5 years CTT (Convertible Tenure Track)
• Full-time (35 hours per week)

The Lecturer reports to the Head of School via the Head of Department.

Specific responsibilities for this role include:

• Actively carry out research in Data Science, Mathematics and Statistics with a view to publication in influential and high-impact scholarly journals.
• Work both collaboratively and independently on research grant proposals and applications to national competitive grant agencies and other funding bodies.
• Develop research collaborations within the School as well as links with other groups on campus and with industry.
• Develop research collaborations nationally and internationally.
• Actively disseminate research findings at seminars and conferences within the School, the UNSW environment, nationally and internationally.
• Supervise Honours and Masters Course Work projects; and supervise PhD and Masters Research students.
• Teach data science, mathematics, and statistics courses to a range of audiences at the University.
• Teach specialist Honours and Masters level courses.
• Contribute to the design and delivery of the School’s face-to-face teaching programs and courses.
• Contribute to the design and delivery of the School’s online teaching programs and courses.
• Actively participate in School activities and demonstrate an ability and willingness take on leadership roles in the School.
• Undertake administrative duties as specified by the Head of School and participate in School, Faculty and/or University committees as required.
• Align with and actively demonstrate the UNSW Values in Action: Our Behaviours and the UNSW Code of Conduct.
• Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on the health and safety of yourself or others. 

About the successful applicant

To be successful in this role you will have:

• PhD or equivalent qualification in relevant mathematical or data sciences.
• Demonstrated research ability in Data Science, Mathematics and Statistics.
• Demonstrated ability to conduct research with other researchers in the School.
• Evidence of effective teaching experience.
• Evidence of research group collaborations.
• Capacity to conduct productive research at an international level.
• Strong publication record in top, peer-reviewed journals.
• A record, or demonstrated ability, of success in external research funding.
• Ability to supervise PhD students.
• Experience in student supervision including, for example, Honours, Masters, Vacation Scholars projects.
• Willingness to engage in teaching into online programs in Data Science and Statistics.
• Excellent oral and written communication skills.

You should systematically address the selection criteria listed within the position description in your application.

Please apply online - applications will not be accepted if sent to the contact listed.

Contact:
Jake Olivier
E: j.olivier@unsw.edu.au

Applications close: March 8th, 2021 

Find out more about working at UNSW at www.unsw.edu.au

UNSW aspires to be the exemplar Australian university and employer of choice for people from diverse backgrounds. UNSW aims to ensure equality in recruitment, development, retention and promotion of staff and that no-one is disadvantaged on the basis of their gender, cultural background, disability, sexual orientation or identity or Indigenous heritage. We encourage everyone who meets the selection criteria to apply.

UNSW partners with Australia’s leading diversity organisations, networks, and campaigns. Please refer to UNSW’s diversity offerings for further information on our flexible work and leave options, and support for carers (childcare, parent rooms, parental leave).