First listed on: 13 July 2017

FSP Postdoctoral Fellowship - analytics on wireless embedded devices

  • Would you like to utilise your skills in Machine learning & apply them to embedded devices?
  • Collaborate with world leading, dedicated professionals in distributes sensing systems, robotics, marine science & biomedical material design!
  • Join a cohort of early career scientist & engineers & pursue high-impact research!

The Position

Launch your Postdoctoral career, extend your professional network and greatly enhance your future in science and technology whilst solving problems in physiological sensing of animal species in marine environments. The postdoctoral fellowship is part of the CSIRO’s Active Integrated Matter (AIM) Future Science platform.  AIM is one of six Future Science Platforms funded by a new CSIRO cross-disciplinary initiative on future science that combines innovation in materials, robotics, sensing, and autonomy. Specifically, the main goal of this project is to develop energy efficient data analytics and machine learning algorithms for distributed embedded systems.

You will develop classifiers for small Internet of Things (IoT) devices, distributed machine learning algorithms that can overcome limitations of individual IoT devices, and algorithms that can augment limited on-board computational resources through calculations on a backend server or GPU cluster. In collaboration with an interdisciplinary research team, you will apply algorithms to tracking animal species in remote environments, in-situ measurements of physiology, health, and behaviour of animals, and indirect inference and monitoring of stressors, diseases, and physiological anomalies in natural ecosystems.

The main application area is to improve CSIRO’s monitoring capability in marine environments, however, the fellow will have an opportunity to apply the algorithms in several exciting environments, such as working with elephants in Africa, jaguars in Amazon rainforest, and water buffalos in north Queensland.

Location: Queensland Centre for Advanced Technologies – Pullenvale, QLD Australia
Salary: AU$78K - AU$88K plus up to 15.4% superannuation
Tenure: 3 year specified term
Reference: 42865

For more details about this exciting opportunity click on the position details link:  Position Details

 To be successful you will need:

  • Demonstrated experience in working with resource constrained devices (e.g., ARM Cortex architecture), energy and resource optimized algorithm design, networked systems.
  • Knowledge of time-series signal processing, statistical data analysis, and sensor fusion.
  • Demonstrated scientific track record in machine learning, including feature selection, model complexity control and dimensionality reduction, and model performance and error analysis.
  • The ability to work effectively as part of a multi-disciplinary, regionally dispersed research team, plus the motivation and discipline to carry out autonomous research.
  • A record of science innovation and creativity, plus the ability & willingness to incorporate novel ideas and approaches into scientific investigations.

Owing to the terms of the fellowship, candidates must not have more than 3 years of relevant full time postdoctoral experience.


At the Commonwealth Scientific and Industrial Research Organisation we do the extraordinary every day. We innovate for tomorrow and help improve today – for our customers, all Australians and the world.

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Find out more

About the Future Science Platforms and the Active Integrated Matter Science Platform

Future Science Platforms (FSPs) are a major new CSIRO initiative and are multi-year investments in frontier science that will help reinvent and create new industries for Australia. The Active Integrated Matter Future Science Platform called AIM is combining materials, robotics, processing and sensing technologies and autonomous science to lead ground-breaking advances at the interface of big data, advanced autonomous systems, and materials science. These inventions and advances will drive the i-manufacturing or manufacturing 4.0 revolution and put early adopter industries ahead of the competition.

How to Apply:  To apply for this position please include with your CV/Resume and a statement addressing the essential criteria, and any other information that is relevant to the position.  Please upload these as one document.  

Applications close:  8 August 2017 (11:59pm AEST)

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