Research Fellow (Postdoctoral), Computational Geospatial Data Scientist

• Part-time (0.6-0.8), Fixed Term position for 2 years (possibility of extension) 

• Academic level B (AU $105,000-125,000 p.a) + 17% Superannuation and Flexible Working 

• Based in the heart of Melbourne (Swanston St) at our City Campus 

About the School 

Located in the heart of Melbourne on RMIT’s City Campus, the School of Global, Urban and Social Studies is one of RMIT’s largest schools within the College of Design and Social Context. 

We are a strongly research active school with research centres of national and international reputation - the Centre for Urban Research and the Social and Global Studies Centre. 
 
For more information see http://www.rmit.edu.au/socialhumanities  

About the Role 

The Australian Urban Observatory (auo.org.au ) was launched in February 2020 at the RMIT Engaging for Impact Conference and has been developed at RMIT as a new online digital planning platform providing social, economic and environmental area-based liveability indicators for the 21 largest cities of Australia. The project is based within the Centre for Urban Research at RMIT University. This unique knowledge translation project is a first of its kind in Australia and requires commercialisation of research knowledge developed into liveability indicators based on a subscription funding partnership business model to ensure long-term funding and financial viability. Policy and practice relevance is also critical to the liveability indicators produced within the project supporting long-term research impact. 

Further info here: https://www.rmit.edu.au/about/our-values/sustainability/sustainable-development-goals/projects/australian-urban-observatory  

Hear from Professor Melanie Davern talking about the AUO: What is the AUO? (youtube.com)  

The Postdoctoral Fellow is critical to success of the project by extending transdisciplinary knowledge and data creation methodologies necessary for the development of new liveability cycling and environmental indicators included in the Australian Urban Observatory.

The role will require a breadth of computer/spatial/data science knowledge across a range of applied disciplines with a focus on the development of new cycling and environmental data sets and applied computational geospatial data analysis to create new knowledge on local neighbourhood cycling infrastructure and environmental living conditions.

We are seeking recent PhDs or soon to graduate PhDs with exceptional promise or Masters level students with applied knowledge with interest in practical applications of academic research in policy and practice settings and research translation as well as traditional research outcomes such as academic papers and presentations.   

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

• Knowledge and experience in computational geospatial science, computer science, and geostatistics 

• Good base knowledge in programming and applied mathematics demonstrated through academic or practice 

• Experience in designing algorithms processing satellite and aerial imagery and familiarity with machine learning algorithms such as the Segment Anything Model will be considered an advantage 

• Excellent programming skills in multiple languages including R and Postgres SQL 

•  Experience in working with open-source data, code, and software 

• Demonstrated ability and practices used in effectively managing and meeting project deadlines and workloads and communicating these across a team  

• Excellent interpersonal and communications skills appropriate for interacting with transdisciplinary AUO team members, staff, students, and industry bodies. 

• Deliver high quality project outcomes, and increasing ability to attract research funding 

• Publications in academic journals and interest or experience in Higher Degree Research student supervision 

Mandatory:

• Recent PhD (graduation within the last 5 years) or near graduation with experience in complementary field(s) or practice including environmental science, remote sensing, applied mathematics or computer science. Masters level qualififcations with significant applied or industry knowledge will be considered.

• High quality knowledge in their PhD discipline or evidence of an area applying data science for new discoveries

• Advanced coding and scripting with excellent knowledge of advanced software engineering, computer science and application of statistics

• Knowledge and experience in R studio and spatial databases

To Apply  

Please submit your CV and letter addressing the Key Selection Criteria numbers 1-5 and 8 and 11 (from the PD) and your suitability for this position by clicking on the ‘Apply’ link at the top of this page.  Note we are prioritising those candidates with Australian

For further information about this position, please see the Position Description hyperlinked below or contact Maria Sortino, Communications & Team Co-ordinator via email [email protected] . 

Link to PD 

Position Description - Postdoctoral Fellow, Computational Geospatial Data Scientist  

Please note: If you are viewing this advert from an external site, please click ‘apply’ and you will be redirected to RMIT's Jobs website to access the Position Description at the bottom of the page. 

Appointment to this position is subject to passing and maintaining a Working with Children and National Police Check. 

Applications close: 4pm, Friday 22 March 2024 

Applications Close:
21 Mar 2024 11.59 pm

RMIT is an equal opportunity employer committed to  being  a child safe organisation. We are dedicated to attracting, retaining and developing our people regardless of gender identity, ethnicity, sexual orientation, disability and age. Applications are encouraged from all sectors of the community and we strongly encourage applications from the Aboriginal and/or Torres Strait Isla n der community.  

At RMIT, we are committed to supporting adjustments throughout the recruitment and selection process, as well as during employment. We actively support and encourage people with disability to apply to RMIT. To discuss adjustment requirements, please contact Kassie (Senior Talent Acquisition Advisor), via [email protected] or visit our Careers page for more contact information - https://www.rmit.edu.au/careers .

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