Join our team: 3-year postdoctoral fellowship on optimizing adaptive management
We are seeking a highly motivated and dynamic postdoctoral research fellow to join CSIRO Ecosystem Sciences’ conservation decisions team to undertake research on optimizing adaptive management decisions under imperfect detection. The postdoctoral research fellow will be supervised by Iadine Chades, Andy Sheppard (CSIRO) and Pr Tom Dietterich (Oregon State University).
Resources to halt global biodiversity decline are still inadequate. Managers of threatened species therefore need guidance on how to best invest their scarce resources to maximise the chance of saving species in the long term. Decision theory is now helping decision-makers prioritise biodiversity threat management across time and space but a major drawback with current decision approaches is their need for “data-hungry” models that simulate how a species or system will behave in the future under different management decisions.
Specifically you will:
- Develop innovative concepts, theories and techniques to facilitate optimal adaptive management over time for hard to detect invasive and threatened species populations.
- Contribute to the development of adaptive management recommendations to help practitioners protect biodiversity.
- Publish findings in high impact journals, present finding at both national and international conferences and participate in interdisciplinary working groups.
- Contribute to a dynamic, innovative and effective research team working with CSIRO Ecosystem Sciences.
- Participate in CSIRO’s postdoctoral training program.
Location: Dutton Park, Brisbane, QLD, Australia
Salary: AUD$81K – AUD$88K plus up to 15.4% superannuation
Tenure: 3 year specified term
To be successful in this position you will need:
- A PhD in artificial intelligence, ecology, conservation, computational sustainability or related field of decision theory (e.g. applied mathematics, computer science, economics or related discipline).
Note: Owing to the terms of CSIRO Postdoctoral Fellowships, you must not have more than 3 years relevant post doctoral experience.
- Demonstrated research achievement in decision theory, optimal resource allocation, adaptive management or ecological modelling. In particular, demonstrated research achievement in one or more of Markov decision processes (MDP), partially observable Markov decision processes (POMDP), stochastic dynamic programming, reinforcement learning and adaptive management.
- Demonstrated ability to initiate research characterised by originality, creativity and innovation. Publish the findings from research in international peer reviewed journals or selective conference proceedings.
- Enthusiasm for applying advanced computational and decision theoretic tools to ecological problems.
- High-level written, oral and interpersonal communication skills, including demonstrated experience in preparing briefings for a range of audiences, and ability to work effectively in a team.