Do you want to work for two of the world's leading research organisations, live in a city with extremely high standard of living, enjoy pristine beaches and sun all year round, and still carry out ground breaking Machine Learning, Robotics research to solve real-world challenges? If so, this position is for you.
A Fully Funded PhD position is available as a part of a research collaboration between the Robotics and Autonomous Systems group at the Commonwealth Scientific and Industrial Organization (CSIRO) and the Queensland University of Technology (QUT), in Brisbane, Australia. You will receive a scholarship of $27,000 per year for 3.5 years. Top-up of $10,000 per year will be awarded to outstanding students.
Simultaneous Localization and Mapping (SLAM) is a key enabling component of driverless vehicles, robotics and augmented reality. SLAM goal is to estimate pose of the vehicle and simultaneously generate dense 3D scene reconstruction. At CSIRO we have developed and deployed state-of-the-art 3D LiDAR-based SLAM systems for the past decade. There is a new direction of research at the intersection of deep learning and geometry-based 3D SLAM. The research in this PhD programme will develop algorithms for geometry-based Deep Learning SLAM in a dynamic and unstructured environment. The PhD programme will involve the development of self or semi-supervised learning methods to address the significant weakness of most current deep networks.
- MUST: a Bachelor’s degree with the first Class Honours or a Master’s degree with Research in a relevant area in the past 5 years (e.g., Computer Science, Electrical Engineering, Mechatronics, Physics or other related fields)
- Strong competencies in one or more of the followings areas: Robotics, Computer Vision, Machine learning, Deep Learning.
- Demonstrated strong programming skills in C++ or Python in Linux.
- Demonstrated Research Experience (for example, a good publication record)
- Experience in Robot Operating System, Pytorch, Tensorflow
How to apply:
Prospective students should send the following documents in a SINGLE PDF file to Dr. Peyman Moghadam (firstname.lastname@example.org) with the subject [PhD Deep SLAM]
- one page cover letter explaining your research background and interests,
- Latest CV or Resume,
- Latest Transcript
About The Robotics and Autonomous Systems and CSIRO
The Robotics and Autonomous Systems at CSIRO has over 80 scientists and researchers, and is a world leader in its field. It develops foundational and applied research in robotics, computer vision, distributed sensing and sensor networks, and autonomous systems for a broad range of domains. It has very well–equipped laboratories with strong engineering support, and a variety of aerial, aquatic, wheeled and legged robotic research platforms. The PhD projects will be conducted with joint supervision of CSIRO and QUT researchers.
The Commonwealth Scientific and Industrial Research Organisation (CSIRO) is Australia’s national science agency and one of the largest and most diverse research organisations in the world. Research spans five broad areas: information and communications; manufacturing, materials and minerals; environment; energy; and food, health and life sciences. CSIRO provides a highly innovative and dynamic research environment, and is positioned in the top 1% of global research institutions in 14 of 22 research fields and in the top 0.1% in four research fields.
For more information about CSIRO’s Autonomous Systems Program visit:
and for more information about CSIRO visit:
About Queensland University of Technology (QUT)
Queensland University of Technology (QUT) is a leading Australian university with “real world” focus in teaching and research and an annual research income of more than $80M. The PhD project will be hosted in the SAIVT research program within the Science and Engineering Faculty (SEF) of QUT. The Faculty has around 1000 higher degree students and provides excellent research facilities and exciting research space in the new $230M Science and Engineering Centre. The SAIVT research program sits within the School of Electrical Engineering and Computer Science and works in delivering world leading research in the areas of computer vision, machine learning, image processing and robotics.
For more details about the SAIVT research program visit: