Research Scientist – Efficient Machine Learning For Time-series Data

The Opportunity
Our Distributed Sensing Systems (DSS) group is one of the leading large-scale sensing and analytics groups in the world, based in Brisbane, Queensland, Australia. We are part of the Cyber-Physical Research Program at CSIRO’s Data61 Business Unit. The group’s research focuses on creating integrated sensing, AI/ML, and telemetry technologies that will radically improve the cost and quality of data gathering on a large scale to enhance the understanding of our natural and built environments.

• An innovative and collaborative workplace with fantastic flexibility
• Work in a world-class research & development precinct
• Join CSIRO and support Australia’s premier scientific organisation!

This is a research scientist position, expected to conduct research on efficient machine learning algorithms for time-series data on edge devices and implement such algorithms on edge hardware, for projects in digital agriculture – eGrazor, digital manufacturing – FDMF/Maven, and smart building/digital twin domains. Specifically, the position will develop lightweight ML models to analyse multi-modal time-series data from multiple edge devices and sensors such as temperature/humidity, or accelerometer, to understand/classify the context in which a sensor device operates, or identify activities of the target object.

Your duties will include:

• Develop multi-variate/multi-modal algorithmic solutions that are suitable for distributed and in-network processing or edge computing.
• Implement and evaluate the developed algorithms and methods efficiently using Python libraries such as scikit-learn, TensorFlow, and PyTorch.
• Liaise with domain scientists/experts to validate algorithms and tools on the appropriate embedded systems or edge computing platforms.
• Publish results in relevant reputable journals and conferences and prepare patent applications.
• Recognise and exploit opportunities for innovation and the generation of new theoretical perspectives, and progress opportunities for further development or creation of new lines of research.

Location: Brisbane (Pullenvale), Queensland
Salary: AU$102,724 to $AU111,165 + up to 15.4% superannuation
Tenure: Indefinite/Specified term of x years/Casual
Reference: 88767

To be considered you will need:
Essential:

• A PhD (or an equivalent combination of qualifications and research experience) in a relevant field.
• Solid knowledge of machine learning (preferably in statistical learning/deep learning).
• Demonstrated experience in models simplification using techniques such as model/knowledge distillation, binarization, etc.
• A sound history of publication in high-rank peer reviewed journals and/or authorship of scientific papers, reports, grant applications or patents, in machine learning or systems areas.
• 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.
• Proficient in Python, C++ or equivalent.
• High level written and oral communication skills with the ability to represent the research team effectively internally and externally, including the presentation of research outcomes at national and international conferences.
• A record of science innovation and creativity, including the ability & willingness to incorporate novel ideas and approaches into scientific investigations.

Desirable:

• Experience or interest in one or more of the following: designing and implementing time-series data analysis/mining algorithms with information theory, statistics or neural networks-based models.
• Good experience with high-dimensional, multimodal time-series data streams.
• Good experience using GPU-assisted model acceleration and source code versioning systems such as Git.
• Experience working in object/event detection, or activity classification.

For full details about this role please view the Position Description

Eligibility
Applications for this position are open to Australian/New Zealand Citizens, Australian Permanent Residents or you must either hold, or be able to obtain, a valid working visa for the duration of the specified term. Appointment to this role is subject to provision of a national police check and may be subject to other security/medical/character requirements.

To enter a CSIRO site, CSIRO will require you to show proof of vaccination against COVID-19 (or show a valid medical exemption from vaccination). If you are unable to meet this requirement, then you must return a negative result on a Rapid Antigen Test (within 48 hours prior to attending site) and wear a face mask whilst on the CSIRO site. These requirements apply if you are attending a CSIRO site as part of a recruitment process.

Flexible Working Arrangements
We work flexibly at CSIRO, offering a range of options for how, when and where you work.