• Work with world-leading machine learning/artificial intelligence scientists
• Apply your knowledge to exciting challenges in spatiotemporal learning
• Join the CSIRO MLAI Future Science Platform (MLAI FSP)

CSIRO Early Research Career (CERC) Postdoctoral Fellowships provide opportunities to scientists and engineers who have completed their doctorate and have less than three years of relevant postdoctoral work experience. These fellowships aim to develop the next generation of future leaders of the innovation system.

In this position you will undertake research in the CSIRO Machine Learning and Artificial Intelligence Future Science Platform (MLAI FSP). As the successful candidate you will develop new machine learning and artificial intelligence methods that have general applicability for spatiotemporal datasets.  The methods will be applied to an exciting challenge in the Mineral Resources Business Unit: Discovering new resources. This science field has large complex, multilayered datasets that have significant analytical challenges.  You will also have the opportunity to work with other members of the CSIRO MLAI FSP Platform on projects ranging across multiple science research areas. You will focus on the advancement and development of artificial intelligence methods and tools to improve generalisation and transferability and algorithms that address large complex, multilayered datasets. You will also work on addressing challenges facing data uncertainty, sparsity and unlabelled data using methods including self-supervised or semi-supervised learning. 

• A doctorate (or will shortly satisfy the requirements of a PhD) in a relevant discipline area, such as machine learning, artificial intelligence, computer vision, computer science, statistics, data analytics, applied mathematics or applied physics.
• Please note: To be eligible for this role you must have no more than 3 years (or part time equivalent) of postdoctoral research experience.
• A sound history of publication in peer reviewed journals and/or authorship of scientific papers, reports, grant applications or patents.
• Solid knowledge of machine learning, artificial intelligence and statistics, and the ability to understand and develop mathematically-founded machine learning algorithms and their development in toolkits such as TensorFlow or PyTorch.
• 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.
• Knowledge of Python, C++ or equivalent.

For full details about this role please view the Position Description