Posts

MoCaO Lectures in Data ScienceMoCaO

MoCaO Lectures:  Data Science, 11-15 July 2022

/in /by

Due to unforeseen problems with the registration system, all registrations for MoCaO lectures up till until the date 29/06/2022 have been lost. To register again, please use the new registration  form on MoCaO lectures webpage.

The inaugural MoCaO Lectures in Computation and Optimisation are focused on Data science and in particular machine learning, its algorithms, mathematical foundations and applications. These lectures are designed to be accessible to novices to the field who have a mathematics and computational background, such as PhD students, postdocs and academics who wish to have a better understanding of recent advances in this dynamic field.

These one hour lectures will be held each day during the week of July the 11 to the 15th and will be scheduled at 12noon AEST on the Monday through to the Thursday and will be starting at 12.30 on the Friday and run for 2 hours that day. All lectures will be broadcast via Zoom.

Speakers

Prof. Stephen Wright:  is the George B. Dantzig Professor of Computer Sciences at the University of Wisconsin-Madison. He is a past chair of the Mathematical Optimization Society and a SIAM Fellow. Currently he directs the Institute for Foundations of Data Science at the University of Wisconsin Madison. Steve is a world renowned expert in optimization and the author of several highly cited books in this field.

Prof. Guoyin Li: is a professor in the School of Mathematics and Statistics at University of New South Wales. He was awarded an Australian Research Council Future Fellowship (for mid-career researchers) during 2014-2018. His research interests include optimisation, variational analysis, machine learning and tensor computations.

Dr. Quoc Thong Le Gia: is a Senior Lecturer in the School of Mathematics and Statistics, UNSW, Sydney. His research interests include Numerical Analysis, Approximation Theory; Partial Differential Equations; Machine Learning and Stochastic Processes.

For more information and to register, please visit http://www.mocao.org/mocao-lectures-data-science/.

Associate Professor/Professor in Statistics or Data Science

/in /by

School of Mathematical Sciences
The University of Adelaide

Closing Date: 12th August 2021

(Level D/E) $147,685 to $189,518 per annum plus an employer contribution of up to 17% superannuation may apply. 

Continuing position available from 1 January 2022.

The University of Adelaide is seeking a senior academic to lead the Discipline of Statistics in the School of Mathematical Sciences and contribute to the School’s strategic priority of expanding its research and educational offerings in data science, broadly construed.

This is an opportunity for an emerging or current academic leader to join a top-ranked team with ambitious plans for the future. The University of Adelaide received the highest possible rating of research quality in the mathematical sciences overall and in each of its disciplines in the two most recent ERA assessments. It was the only Australian university to receive top ratings for engagement and impact in the mathematical sciences in the 2018 Engagement and Impact Assessment.

The School is committed to pedagogical innovation and is currently working with its Industry Advisory Board to strengthen its external engagement as a strategic priority.

The School is strongly committed to increasing the diversity of its staff and students. We encourage and warmly welcome applications from academics who are able to contribute to the diversity of the School community. For more information and to apply, go to:
https://careers.adelaide.edu.au/cw/en/job/505815/associate-professorprofessor-in-mathematical-sciences

Lecturer in Data Science and Statistics

/in /by

The School of Mathematics and Statistics
University of Melbourne

Closing Date: 15th December 2020

The School of Mathematics and Statistics is seeking to expand its expertise in data science and contemporary statistics.

The successful applicant is expected to develop and maintain a high-level research program in data science and statistics. Beyond the Data Science and Statistics groups, the University of Melbourne provides an outstanding environment in which to develop innovative research in data science and statistics, with opportunities for collaborations in the Melbourne Centre for Data Science, with machine learning and bioinformatics researchers in Computing and Information Systems, biostatisticians in Population and Global Health, big data research in genomics in the Melbourne Integrative Genomics research hub as well as applied and theoretical approaches to big data in the Australian Research Council (ARC) Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). The School has excellent computing facilities and access to both local and cloud high performance computing clusters.

The candidate should also have a strong commitment to teaching and the supervision of research students. Teaching will occur within the School of Mathematics and Statistics undergraduate and MSc programs, and the applicant will be expected to teach statistics and its applications to a variety of audiences. They are also expected to supervise research students at undergraduate, MSc and PhD levels in data science and statistics.

To be considered for this role you will have completed a PhD or equivalent research higher degree in statistics or related discipline and demonstrated research excellence in relation to career stage.

This is a full-time fixed-term position for 3 years.

For more information and to apply, click here.