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Research Assistant /Associate in Model-Based and Data-Driven Controller Synthesis for Hybrid Systems

Newcastle University - School of Computing

Location: Newcastle upon Tyne
Salary: £28,331 to £35,845 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 22nd July 2021
Closes: 16th September 2021
Job Ref: 9734

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

The Role
This is an exciting opportunity to join the School of Computing as a Research Assistant/Associate in the EPSRC project ‘CodeCPS: Correct-by-Design Estimation and Control of Cyber-Physical Systems’. The main aim of the project is to advance the theoretical foundations of correct-by-design controller synthesis for hybrid/stochastic systems. With the rapid embedding of software in engineering of dynamical systems, traditional design methodologies are lagging far behind in efficient development of multi-layer, multi-objective, adaptive, nonlinear dynamical systems. A promising direction to address this issue is to use correct-by-design methodologies that are founded on mathematical models and provide guarantees on the correctness of the controller once it is implemented. CodeCPS will address three specific challenges faced by correct-by-design synthesis: complex dynamics, large number of interacting components, and presence of uncertainty (lack of precise mathematical models, unpredicted phenomena in the environment, and incomplete state information). This project will use the class of "hybrid models" that can capture the behaviour of components with discrete and continuous variables, and their interactions. Possible application domains for the results include autonomous vehicles and frequency regulation of smart grids.

You will work on the following topics:

  1. Develop methods for synthesising controllers that are correct by design, have incomplete state information and are robust to model uncertainty.
  2. Develop methods for synthesising controllers applicable to systems with large number of components and state variables using decomposition and assume-guarantee reasoning.
  3. Develop AI planning and machine learning methods with formal guarantees (e.g., convergence or sample complexity) for performing synthesis on unknown models or unknown objective functions.
  4. Implement the new approaches as a set of software design tools which support the construction, integration, safety and performance analysis of the system.

For more information about the research at HyCoDeV Lab Please click here. For more information on the research in the EPSRC project, please click here.

More information School of Computing and our research, please click here.

This position is available on a full time and fixed term basis for 24 months.

Interested candidates should first contact Dr Sadegh Soudjani at to discuss their application. Please include your cover letter and CV and title your email “[CodeCPS-PDRA]” in the subject of your email.

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