Hyperspectral Deep Learning-Funded PhD opening
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 $37,000 per year for 3.5 years.
Topic: Hyperspectral Deep Learning
Hyperspectral cameras are currently undergoing a change from bulky and expensive equipment towards mobile and portable devices. A hyperspectral camera comprises of hundreds of bands with shortwave dependencies.
Compared to conventional colour cameras (RGB bands), one could use these shortwave dependencies to design and develop a deep network for object classification, semantic segmentation and scene understanding.
Both spectral and spatial relationship needs to be modelled by the deep networks simultaneously. The research in this PhD programme will develop algorithms for hyperspectral deep learning.
The PhD programme will involve the development of learning with self-supervision algorithms to address the significant weakness of most current deep networks.
- Must have 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 e.g. a good publication record.
- Experience in Pytorch and 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 hyperspectral], including:
- a current c.v.
- details of grades or an academic transcript
- one page cover letter explaining your research background, interests to this PhD topic,
Dr. Peyman Moghadam (email@example.com)