Research Fellow in AI-Driven Inference for Gravitational Waves University of Nottingham Nottingham, United Kingdom

University of Nottingham, The Park, City of Nottingham

Research Fellow in AI-Driven Inference for Gravitational Waves University of Nottingham Nottingham, United Kingdom

Salary not available. View on company website.

University of Nottingham, The Park, City of Nottingham

  • Full time
  • Permanent
  • Onsite working

Posted today, 30 Oct | Get your application in now to be one of the first to apply.

Closing date: Closing date not specified

job Ref: 5b6e070c87624b31b79aaf0479c8de82

Full Job Description

We are looking for a researcher, whose expertise lies in gravitational waves or machine learning, to work with Dr Stephen Green on a UKRI FLF-funded project "AI-Driven Inference for Gravitational Waves: Accelerating Discoveries in Fundamental Physics". The aims of the project are to develop AI tools to analyse gravitational-wave data quickly and accurately, and apply these tools for discovery in astrophysics, cosmology, gravity, and fundamental physics. 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. The School is committed to creating opportunities for people traditionally under-represented in Mathematical Sciences and strives to maintain an environment where people can be their authentic selves.You will be able to carry out duties to the highest standard and to evidence how through your experience you will:

  • Undertake original research of international excellence.
  • Develop research objectives and proposals for own and/or collaborative research area.
  • Prepare papers for publication in leading journals and/or contribute to the dissemination at national/international conferences, workshops and meetings resulting in successful research outputs.
  • Identify opportunities and assist in writing bids for research grant applications. Prepare proposals and applications to both external and/or internal bodies for funding, contractual or accreditation purposes.

    A PhD, or equivalent, in physics, astronomy, computer science, mathematics, statistics, or a closely related discipline. Candidates may be near completion but must have their PhD awarded prior to starting post.
  • Expert knowledge of gravitation or machine learning for science. This should include one or more of the following: gravitational-wave modelling or data analysis, black hole physics, mathematical or numerical relativity, statistical inference, or deep learning.
  • Excellent communication and organisational skills.
  • The ability to work independently and as part of a multidisciplinary and multicultural team.
  • Networking, actively engaging with and valuing other areas and diverse groups.