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You will join our EPSRC-funded project Sampling in Hereditary Classes that proposes to bring together two previously distinct areas of fundamental research in algorithms and computational complexity: algorithms for random generation and approximate counting, and structural graph theory.
You will contribute to a theoretical research project on randomized sampling algorithms in graph classes, led by Dr Haiko Müller and Prof Martin Dyer. This is a joint project with Prof Mark Jerrum (QMUL). Your main task will be to design and explore an information system documenting the new results obtained and related existing knowledge on counting problems.
Holding a PhD in Computer Science you will have a background in graph algorithms, graph algorithms and theoretical concepts. You will have hands on experience with the use of database systems and implementation of user interfaces.
What we offer in return
- 25 days holiday plus 15.5 Bank Holidays/days that the University is closed by custom (including Christmas) – That’s over 40 days a year!
- Pension schemes with a generous contribution from the University.
- Health and Wellbeing: Discounted staff membership options at The Edge, our state-of-the-art Campus gym, with a pool, sauna, climbing wall, cycle circuit, and sports halls.
- Personal Development: Access to courses run by our Organisational Development & Professional Learning team, and self-development courses including languages, Creative Writing, Wellbeing Therapies and much more.
- Access to on-site childcare, shopping discounts and travel schemes are also available.
And much more!
To explore the post further or for any queries you may have, please contact:
Dr Haiko Müller , Senior lecturer
Tel: +44 (0)113 343 5445 or email: [email protected]
Location: Leeds - Main Campus
Faculty/Service: Faculty of Engineering & Physical Sciences
School/Institute: School of Computing
Category: Research
Grade: Grade 7
Salary: £34,304 to £40,927 p.a.
Due to funding restrictions, an appointment will not be made higher than £36,382 p.a.
Working Time: 37.5 hours per week
Post Type: Full Time
Contract Type: Fixed Term (6 months (grant funding))
Release Date: Friday 24 June 2022
Closing Date: Sunday 03 July 2022
Interview Date: To be confirmed
Reference: EPSCP1102
Downloads: Candidate Brief
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