Rebecca Lange1, CIC data scientist team2
1Curtin Institute for Computation, Curtin University, Perth, Australia, email@example.com
2Curtin Institute for Computation, Curtin University, Perth, Australia, firstname.lastname@example.org
In the era of ever growing data and interconnectivity, computation fundamentally underpins the majority of internationally competitive research across all fields and disciplines. As the demand for computational skills has grown, so too has the need for dedicated support for the research community. The Curtin Institute for Computation (CIC) was therefore established to meet this increasing demand at Curtin University.
The CIC is a truly multidisciplinary institute, inspiring and fostering collaboration across computer science, engineering, sciences, business, social sciences and the humanities. It has five themes; big data analytics, simulation, modelling and optimisation, visualisation, and education.
While the CIC is a virtual institute, it has a core team of data scientists who assist Curtin University researchers across all fields with their computational modelling, data analytics, and visualisation problems. Furthermore, the CIC data scientists are actively involved in creating opportunities for researchers to network and share ideas, and they develop and oversee computational training offered by the institute.
In this e-poster we provide an overview of the structure of the CIC and its achievements since the core data science team became operational in 2016. Furthermore, the poster will offer the opportunity to explore several case studies from across the institute, highlighting the need for, and success of, a central data scientist team supporting researchers from all fields.
Rebecca Lange received her PhD in astronomy from the International Centre for Radio Astronomy Research at the University of Western Australia.
Before Rebecca moved to Australia she studied Astronomy and Physics at Nottingham Trent University where she also worked as a research assistant in scientific imaging for art conservation and archaeology. Her work there included the development and testing of instruments and software for imaging and spectroscopy as well as the organisation and supervision of field trips, which often required liaising with art curators and conservators.
Throughout her studies and research Rebecca has gained extensive programming as well as data analytics and visualisation experience in various programming languages.
Currently she is working as a data scientist for the Curtin Institute for Computation where she helps researchers by providing data analytics and computational support and training.