Fast multi-wavelength variability of accreting compact objects

Eligibility: UK/International (including EU) graduates with the required entry requirements

Duration: Full-Time - between three and three and a half years fixed term

Interview date: Will be confirmed to shortlisted candidates

As matter falls onto compact objects like black holes and neutron stars, due to the presence of turbulence, matter emits a huge amount of strongly variable radiation. The development of fast-readout optical and infrared cameras has made it possible to study X-ray binaries on timescales down to sub-second, and to compare their variability directly with the X-rays. This has opened a new window on the accretion–ejection process.

For instance in recent years, it has allowed strong constraints to be placed on the properties of the jet and inner accretion flow around both black holes and neutron stars.

The successful candidate will work with strictly simultaneous multiwavelength observations of black hole and neutron star X-ray binaries, obtained with XMM-Newton, NICER and Insight-HXMT in the X-rays, HAWK-I at the VLT in the infrared, and HiPERCAM at the GTC and ULTRACAM at the NTT in the optical. Using time-series analysis techniques in both the time and Fourier domains, the student will extract key physical information on the accretion flow and jet in these systems.

Modelling of the observed variability will then be used to place tight constraints on fundamental parameters such as the jet speed, the inner disc truncation radius and the magnetic field strength.

Tuition fees and bursary

The successful candidate will receive comprehensive research training including technical, personal and professional skills. All researchers at Coventry University (from PhD to Professor) are part of the Doctoral and Researcher College, which provides support with high-quality training and career development activities.

You're invited to become part of the Coventry Centre for Doctoral Training in AI (C-CDT AI ): a dynamic, collaborative hub uniting AI staff and PGR researchers from across the University.
As a C-CDT member you'll benefit from structured AI training (from core research methods to ethics and innovation), interdisciplinary peer networks, specialist supervision, shared GPU/cloud resources, workshops, seminars and industry-focused challenge projects.
This additional training and community, complements your home research centre programme, accelerates your technical and professional development, and connects you with a broad AI research ecosystem tackling impactful problems across sectors.

• A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the project element or equivalent with a minimum 60% overall module average.

PLUS

• The potential to engage in innovative research and to complete the PhD within 3.5 years.
• A minimum of English language proficiency (IELTS academic overall minimum score of 6.5 with a minimum of 6.0 in each component).

• Master's or equivalent degree, astronomy/astrophysics or physics
• Experience in coding and data analysis
• Experience with time-series and/or large data sets
• Experience with data reduction of X-ray or optical-infrared observations

Priory Street
Coventry CV1 5FB

United Kingdom