James Cook University has been awarded an Advance Queensland Innovation Partnerships (AQIP) to investigate a machine learning approach to terrestrial based geolocation with CSIRO for Ceres Tag. The project will see the development of an ultra-low power ear tag capable of lasting years on a single battery charge, with a range of at least 10 kilometers. While time of arrival triatelation is a well understood approach, our system will correct multipathing errors by applying machine learning neural networks using real time fixed location and environmental data. We will focus on freely available spectrum to reduce cost to end users, with location resolution of 30 meters and a range in excess of 10 km. We are working in collaboration with CSIRO at the Lansdown research facility outside of Townsville as part of our continued efforts to explore technologies for the Digital Homestead. CSIRO are also developing additional technologies for Ceres Tag that are directly allied to our research project, learn more about their efforts at CSIRO Animal Science and Data61.
Two positions are currently available and will allow successful candidates to:
- Join a leading research project that combines GIS, Radio Geolocation and Machine Learning.
- Collaborate with CSIRO, JCU and Industry researchers and engineers on a collaborative project funded by the Queensland State Government.
- Take this opportunity to grow your expertise in the emerging field of Machine Learning.
CSIRO - AQIP Software Engineer
IoT technologies coupled with machine learning are a growth sector for the tech industry, groups are working across the globe to establish leadership in low power long range geolocation techniques that do not require orbital solutions. An opportunity exists for a highly motivated and creative individual to join CSIRO and JCU to develop location technologies for the livestock industry. This Townsville based job will be at a postdoctoral level with employment through CSIRO.
JCU - AQIP Software PhD Candidate
Join our research team as a Software Engineering PhD candidate and contribute to the developing field of machine learning.
To find out more, contact Professor Ian Atkinson:
Phone: (07) 4781 4551 (+61 7 4781 4551)