Research Associate in Deep Learning for Computational Imaging in Astronomy and Beyond
Research Associate in Deep Learning for Computational Imaging in Astronomy and Beyond
Heriot-Watt University
Edinburgh, United Kingdom
Detailed Description
The Biomedical and Astronomical Signal Processing (BASP) laboratory at Heriot-Watt University Edinburgh (HWU), headed by Professor Yves Wiaux, is recruiting a postdoctoral researcher in computational imaging.
The position is open in the context of a large research project aiming to develop a new generation of computational imaging algorithms intended to deliver simultaneously precision, robustness, efficiency, and scalability of the image formation process. The algorithms will be developed leveraging cutting-edge deep learning and optimisation techniques, as well as high-performance computing implementations. They will be validated for applications in both radio astronomy and magnetic resonance imaging in medicine.
Key Duties and Responsibilities
The postholder will develop new image formation algorithms for radio astronomy. Technology transfer to magnetic resonance imaging in medicine is a secondary target. Outstanding candidates are also welcome to propose their own research project in the broader context of deep learning for computational imaging. Upon outstanding performance, postholders can be granted opportunities for secondments in one of the collaborating institutions and/or to co-supervise a PhD student. A secondary affiliation to EPFL or UoE may be offered to candidates with the appropriate profile.
Education, Qualifications and Experience
We are looking for outstanding candidates with a PhD in physics, electrical engineering, applied mathematics, computer science, or a related discipline.
The candidates will have expertise in computational imaging, with: (i) an algorithmic focus, with particular interest in methods at the interface of deep learning and optimisation theory, and/or (ii) an application focus in radio astronomy, including both simulation and real data processing expertise.
Competence in specific algorithmic approaches such as generative models, or specific applications such as connected or very long baseline interferometry, is of particular interest.
Essential Criteria
- PhD: Hold a PhD (or be about to)
- Area of Expertise: Computational imaging
- Motivation: Energy and enthusiasm
- Evidence of research ability: capability to be self-directed and think innovatively
- Publication record: strong publication record
- Work environment: experience of multi-cultural work environment; ability to work as part of a team
- Communication skills: ability to present work effectively (written/oral)
- Supervision: experience of PhD student supervision.
Desirable Criteria
- Excellence in several of the essential criteria
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