Research Scientist · Algorithm Design & Image Processing
Light Bridges invites applications for a Research Scientist position within CORVUS, a project developing an end-to-end GPU-accelerated platform for the detection and characterisation of fast-moving, very faint objects (near-Earth objects and space debris), advancing global Planetary Defence capabilities. Coordinated by Light Bridges with the Instituto de Astrofisica de Canarias (IAC) and the Universidad de Oviedo (UniOvi). This role leans towards algorithm design and image processing: synthetic tracking search strategies, PSF handling, image differencing, and turning stacked detections into a trustworthy candidate list.
Key details
- Reference: LB-CORVUS-02
- Employment type: Full time, indefinite contract
- Location: Remote, open to applicants based in Spain
- Start date: 01/11/2026
- Application deadline: 27/09/2026
- Salary: approx. €39,700 gross/year
- Contract funded through February 2029
Requirements
PhD in any quantitative discipline obtained before end of 2026; hands-on GPU-accelerated computing experience; strong Python; professional-level English.
Nice to have
signal/image processing (deconvolution, matched filtering, source detection), machine learning for candidate classification, observational astronomy experience, Solar System science or Space Situational Awareness background.
Responsibilities
Work on CORVUS, an end-to-end GPU-accelerated platform for detecting fast-moving, faint near-Earth objects and space debris, leaning towards algorithm design and image processing: synthetic tracking, PSF handling, image differencing. Take part in observing proposals, co-author scientific publications, and contribute to the discovery of new Solar System objects, working alongside a group of 6 to 10 astronomers, software engineers and researchers.
How to apply
Send a CV and a short letter (max. 2 pages) to , stating what you could bring to the project and how your profile fits it. Questions about the position are welcome at the same address. Links to code, repositories, benchmarks or papers you are proud of are more useful to us than long lists of courses.
