Contact: stephen.green2[AT]nottingham.ac.ukLocation: Nottingham, UK
The University of Nottingham Digital Research Service invites applications for a research software engineer (RSE) position in machine learning for gravitational waves. The post is for two years.
The successful applicant will work under the supervision of Dr. Stephen Green and will be funded by his UKRI Future Leaders Fellowship. The project, titled “AI-Driven Inference for Gravitational Waves: Accelerating Discoveries in Fundamental Physics,” focuses on developing state-of-the-art AI tools for fast-and-accurate gravitational wave inference and applying these tools for discoveries in astrophysics, cosmology, gravity, and fundamental physics. The RSE will play a crucial role in advancing the DINGO package for simulation-based inference of gravitational waves (https://github.com/dingo-gw/dingo), contributing to a collaboration involving over 10 researchers across four institutions. Additionally, the RSE will have the opportunity to mentor team members in software engineering practices and support the development of strong coding and project management standards.
Applicants should hold a postgraduate degree in physics, astronomy, computer science, mathematics, or related discipline. We are looking for an RSE with a background in scientific computing, and knowledge of machine learning for science or gravitational waves is desirable.
Successful applicants will join the expanding Nottingham Centre of Gravity (NCoG), which unites gravitational physics expertise across the School of Mathematical Sciences and the School of Physics and Astronomy. NCoG is structured around six core pillars: fundamental physics, mathematics, cosmology, relativistic astrophysics, experiment, and data and modeling. The Centre comprises 17 permanent staff, including Dr Miguel Bezares (numerical relativity), Dr Stephen Green, Dr Laura Sberna (gravitational waves, black holes, and environmental effects), and Prof Thomas Sotiriou (gravitational waves, black holes, and alternative theories), as well as typically 7-8 postdocs and 25 students. Staff are active members of the LIGO, LISA, and ET collaborations, providing ample opportunities for international collaboration and impact.
We believe that talented and inclusive teams deliver the highest quality research and are seeking applications from high-quality candidates who enhance the diversity of our existing team. To that end, we welcome and support applicants requiring flexible working arrangements.
Application process: Interested applicants can access additional information and the application form from the link provided.
Deadline: 28 November 2024.
Informal enquiries may be addressed to Dr Stephen Green.
We look forward to your application!