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Research Associate in Optimization under Uncertainty

Imperial College London - Imperial College Business School

Location: London
Salary: £37,486 to £46,499 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 21st February 2019
Closes: 24th March 2019
Job Ref: BUS00138

The Salary structure is subject to change effective from 1st April 2019, please see full details on our salary structure reform.

Campus: South Kensington, London

Job Summary:

The Management Science & Operations group at Imperial College Business School is seeking applications for a Research Associate in the area of optimization under uncertainty, in particular in the fields of (distributionally) robust optimization and stochastic programming, with applications to energy systems. Applicants must hold a PhD in Operations Research, Applied Mathematics or a related field and have strong mathematical skills.

You will conduct research with Dr. Wolfram Wiesemann from the Management Science & Operations group at Imperial College Business School. The position is funded through EPSRC grant EP/R045518/1, which is conducted in collaboration with researchers from the Energy Futures Laboratory as well as several other departments at Imperial College London.

The Management Science & Operations group at Imperial College Business School studies all aspects of theoretical and practical decision-making, with applications to operations management, energy and finance. Faculty members regularly publish in leading academic journals such as Management Science, Operations Research, Mathematical Programming, Mathematics of Operations Research and SIAM Journal on Optimization. The group maintains close relations with the Computational Optimization Group at the Department of Computing, Imperial College London.

Duties and responsabilities:

  • You will work as part of an international multidisciplinary research team
  • You will conduct methodological research and publish papers on stochastic programming and/or (distributionally) robust optimization.
  • You will apply the aforementioned research to energy models, in collaboration with other researchers from the IDLES project.
  • You will be responsible for drafting academic papers along with interim and final reports on the progress of the work
  • You will present results to a variety of audiences including research funders, academics, and policy makers, at seminars, national and international conferences
  • You will have joint authorship of academic papers from your research, which will be published in leading international journals

Essential requirements:


You should have proven knowledge and skills in operations research, applied mathematics or a related field and possess strong mathematical skills. Applicants with a proven knowledge and expertise in one or more of the following will be preferred:

  • Stochastic Programming
  • (Distributionally) Robust Optimization
  • Modelling of Energy Systems

Skills and Abilities

  • Excellent written and verbal communication skills
  • Excellent inter-personal skills
  • Excellent management and liaison skills
  • Ability to organise own work with minimal supervision
  • Ability to prioritise own work in response to deadlines
  • Demonstrable evidence of initiative
  • Ability to travel within the UK and overseas to attend research meetings

Please see the Job Description for a full list of requirements.

Further information:

The position is full time and fixed term for 18 months.

The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see

Imperial College is committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment. We are an Athena SWAN Silver award winner, a Stonewall Diversity Champion, a Disability Confident Employer and work in partnership with GIRES to promote respect for trans people.

Closing date: 24/03/2019

To apply, visit and search by the job reference BUS00138.

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