澳洲墨尔本皇家理工学院博士后职位—“应急管理人群监测”项目

Research Fellow

Royal Melbourne Institute of Technology

Description

The Research Fellow will support the research and development aims of the Collaborative project between RMIT and Elbit Systems of Australia Pty Ltd (Elbit, ELSA) titled “Crowd monitoring for Emergency management”. Specifically, the research aims to develop computer vision technology for crowd counting and tracking in challenging urban environments using aerial cameras to facilitate pedestrian evacuation modelling.

People counts and locations are key input data for evacuation models used for both evacuation planning before and real-time decision-making during hazard events. These data can be used to initially configure model scenarios as well as calibrate the model’s predictions as conditions change during an event. It is proposed that these data can be obtained live, using cameras (visual and thermal) onboard an Unmanned Arial Vehicle (UAV).

The Research Fellow will work with research teams and partnerships in the School and Research Institutes. You will be required to undertake research activities in line with the University’s research strategy. The position will carry out independent and/or team research that has a significant impact in the area of their specialisation and be acknowledged at a national level as being influential in expanding the knowledge of their relevant discipline.

The Research Fellow’s role is primarily to plan, develop and engage in high quality research projects that are aligned with the University’s research focus areas. You will embed their research expertise into the life of the School through the development of high-quality, productivity-driven research networks across RMIT and with local and national, internal and external partners. You will be expected to engage in high quality research projects and produce high quality outputs.

To be successful in this position, you’ll have as a minimum:

  Evidence of top quality research output including journal publications (e.g. IEEE PAMI, IEEE TIP, IEEE T-ITS), conference contributions (e.g. CVPR, ICCV, ECCV) and/or technical reports in the fields of computer vision and machine learning.

  Experiences in using large synthetic datasets to develop practice computer vision applications that adapt to real environments.

  Ability to work autonomously whilst displaying a strong commitment to work in a team environment, including the demonstrated ability to confidently and effectively work with colleagues, project team leaders, and industry partners.

  Demonstrated ability to meet deadlines and effectively manage varying workloads and respond to changing priorities as required.

  Strong analytical and programming skills, and ability to carry out both theoretical and experimental work.

Please Note: Appointment to this position is subject to passing a Working with Children Check.

About the College

Computer Science, Software Engineering, Data Science, and IT programs at RMIT University are offered in the School of Computing Technologies, one of Australia’s largest and leading educational facilities in the field. In the 2020 QS University Rankings by discipline, RMIT University was ranked top 150 globally for Computer Science and Information Systems. RMIT University prides itself on the quality of its graduates, achieved through programs that have a strong emphasis on both theory and practice, and seeks to make a significant contribution to computing and IT education and research. The teaching programs of the Computing Technologies disciplines cover a wide range of pertinent areas including programming languages and methodology, software engineering, computer architecture, systems analysis and design, theory of computation, data science, database systems, games and graphics, artificial intelligence, data communications and networks, operating systems, web based computing, search engines, and computer and network security.

There are three discipline clusters in the School of Computing Technologies:

  Artificial Intelligence

  Cloud, Systems & Security

  Data Science

More information on the School of Computing Technologies can be found at:

https: // www. rmit.edu.au/about/schools-colleges/computing-technologies

To Apply

Please submit your CV and covering letter addressing the Key Selection Criteria for this position by clicking on the ‘ ‘ link below.

For further information about this position, please see Position Description below or contact Dr Ruwan Tennakoon via email ruwan.tennakoon@rmit.edu.au.