Research Associate in Control Engineering (Dynamically Adaptive Water Supply Networks)

Imperial College London - Department of Civil and Environmental Engineering

Research Associate in Control Engineering (Dynamically Adaptive Water Supply Networks)

Salary Range: £36,800 – £44,220 per annum*

Fixed Term appointment for up to 36 months (with the possibility of extending the contract)

Imperial College London is a science-based institution with the greatest concentration of high-impact research of any major UK university.

Urban water systems face major challenges in providing safe and reliable water supply due to increasing population (demand), ageing infrastructure and climate change.

Dr Ivan Stoianov and his InfraSense Labs team (, Civil and Environmental Engineering Department at Imperial College London, have pioneered advances in sensor and control technologies in order to gain extraordinary insights into the operation of complex water supply networks and facilitate their dynamically adaptive control. The research group is at the forefront of developing and implementing novel simulation and optimisation methods that make use of this new knowledge about the dynamics of large-scale water supply systems and the ability to robustly control their operation.

This post is part of a 5-year EPSRC-funded programme of work (led by Dr Ivan Stoianov, to progress the development of fundamental scientific methods for the design, optimisation and control of next generation resilient water supply networks that dynamically adapt their connectivity, hydraulic conditions and operational objectives. The current post is suitable for someone with a background related to the mathematics of robust control.

Education, Skills and Knowledge

  • PhD degree (or equivalent) in a relevant field such as: control engineering, chemical process engineering, computer science and/or applied mathematics with in-depth knowledge of the mathematics of robust control.
  • Proven ability to publish research in high impact journals.
  • Excellent programming skills (e.g. Matlab, Python, C/C++) with knowledge of software configuration management (e.g. GitHub).
  • Work in a planned way, and implement responsible data, information and software management associated with the research programme.
  • Integrate with the interdisciplinary team of researchers in pipe hydraulics, control engineering and mathematical analysis; and contribute to the mathematics of robust control.
  • Communicate effectively with academic and industrial partners.

Main Duties and Responsibilities

  • Support and co-lead fundamental and applied research in robust and adaptive control algorithms for the design and operation of dynamically adaptive water supply networks (complex networks).
  • Work on the development of novel and tailored control algorithms, their performance evaluation and comparison in order to meet multi operational objectives for the management of complex water supply networks, produce scientific journal publications describing the methods and results in collaboration with internal and external researchers, and present the work at international conferences.
  • Work closely with other RAs and PhD students from the InfraSense Labs research group to enhance and utilise current experimental research in order to generate benchmark models and validate the developed control algorithms in operational water supply networks.
  • Actively contribute to the development of control ideas for dynamically adaptive and resilient networks, and strengthen the related interdisciplinary research activities of the InfraSense Labs research group.

*Candidates who are close to completion of their PhD will be appointed as Research Assistant within the salary range £32,380 - £34,040 per annum.

For enquiries about the post please contact Dr Ivan Stoianov: (

Our preferred method of application is online via our website. Please visit (Select “Job Search” then enter the job title or vacancy reference number into “Keywords”). Please complete and upload an application form as directed quoting reference number EN20170303LE.

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