Postdoctoral Research Associate

The University of Edinburgh - College of Science and Engineering - School of Mathematics

Postdoctoral Research Associate in Data-Driven Portfolio Risk Management

Applications are invited for a 20-month postdoctoral position in the areas of computational mathematical finance, machine learning and optimization with a particular focus on probabilistic and optimization data-driven methods used in portfolio theory. The position will be based at the School of Mathematics, University of Edinburgh.

The successful candidate will join a team of four mathematicians: Sergio García Quiles, Jacek Gondzio, Joerg Kalcsics and Sotirios Sabanis who bridge between the Edinburgh Research Group in Optimization ( and the Probability group (

The project is funded by the EPSRC Impact Acceleration Account and Standard Life Investments ( and will involve research in data-driven portfolio construction approaches to optimal diversification. The project is a step towards a strategic partnership between Edinburgh University and Standard Life Investments (SLI) focused on quantitative portfolio and investment research. There will be opportunities to interact with SLI in order to enhance understanding of practical research implications and aid further career development.

The position is full time and fixed term for 20 months and should be taken up in July 2018 or soon after.

The starting salary will be in the range of £32,548 - £38,833 per annum, depending on experience.

Please include a CV and research statement with your application and arrange for two referees to send letters of recommendation to by the closing date.

Informal enquiries:

Prof Gondzio: +44 131 650 8574, Dr Sabanis: +44 131 650 5084,

The University of Edinburgh promotes equality and diversity, holds a Bronze Athena SWAN award and supports the LMS Good Practice Scheme. We strive for a family-friendly School of Mathematics.

Closing date: Thursday 10th May 2018 at 5pm (GMT)

For further particulars and to apply for this post please click on the 'apply' button below

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