- Use your ecological & statistical skills in a role that contributes to wildlife management issues
- Be part of research into ecology & management of native & invasive vertebrate species
- Make a difference at CSIRO - Australia's premiere Science & Technology Research Organisation
We are seeking a Quantitative Ecologist to join the Living Landscapes Program as a member of the Sustainable Northern Australia Team, based in Townsville. You will primarily undertake research focused on developing ecologically-based approaches to wildlife management issues. Existing projects are large, transdisciplinary, multi-institutional and multi-governmental efforts which have a major impact on government and industry policy and action. Indigenous collaboration and co-development of research is a strong feature of the Team’s work.
In this role, you will contribute your high-level ecological and statistical skills to a range of projects undertaking innovative research into the ecology and management of native and invasive vertebrate species. Current projects include the design and implementation of long-term, national-scale threatened species monitoring programs, understanding movement and resource use of mobile vertebrates to better address current and future management needs, and the development of new land management tools for feral animals in Northern Australia.
Your duties will include:
- Working with internal and external stakeholders to co-develop research products that support ecologically-based wildlife management strategies.
- Providing original quantitative analyses to understand species population dynamics, the effectiveness of management actions and to help guide complex interactions among species and humans.
- Contributing to and/or leading scientific research that integrates spatial data, field collected data and remote data-streams to enhance environmental management outcomes.
- Translating complex data and analytical outputs into easily interpreted end-products for use by non-scientific stakeholders
Location: Townsville, QLD
Salary: AU$113k - AU$132k plus up to 15.4% superannuation
Tenure: Specified term of 3 years
To be considered you will need:
- A PhD (or an equivalent combination of qualifications and research experience) in a relevant field such as ecology, quantitative ecology, behavioural ecology, etc.
- A current driver’s licence.
- A strong ecological background, including field and experimental design skills, and an on-going interest in field-based research, as well as the ability to use ecological concepts to address environmental issues.
- Highly developed skills in the general areas of data-driven modelling and programming, ideally including some area of special expertise e.g. spatial statistics, movement analysis, or developing mathematical models of ecological processes.
- The ability and drive to undertake original, creative and innovative research by generating and pursuing novel ideas and solutions to scientific research problems, and following through to published reports and papers.
- Experience transforming complex data and concepts into easily interpreted end products for policy makers and non-scientific stakeholders.
For full details about this role please review the Position Description.
To be eligible for this role, you must be Australian/New Zealand Citizen or an Australian Permanent Resident currently residing in Australia.
The successful applicant will be required to obtain and provide a National Police Check or equivalent, and undertake a pre-employment medical examination prior to commencement.
Flexible Working Arrangements
We work flexibly at CSIRO, offering a range of options for how, when and where you work. Talk to us about how this role could be flexible for you. Balance
Diversity and Inclusion
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How to Apply
Please apply on-line and provide a cover letter and CV that best demonstrate your motivation and ability to meet the requirements of this role.
Friday 23rd April 2021, 11:00pm AEST
- Closing Date:
- 23 Apr 2021
- QLD - Townsville
- AU$113k - AU$132k plus up to 15.4% superannuation
- Work Type: