Research Associate

Job summary

Applications are invited for the post of Research Associate in Autonomous Vehicle Operations to join the Transport Systems & Logistics Laboratory, part of the Centre for Transport Studies, in the Department of Civil & Environmental Engineering at Imperial College London. This is an exciting opportunity to build theoretical and practical experience in the cutting edge of autonomous vehicle operations, with particular emphasis in multi-vehicle...

Job listing information

  • Reference ENG01445
  • Date posted 30 October 2020
  • Closing date 29 November 2020

Job description

Job summary

Applications are invited for the post of Research Associate in Autonomous Vehicle Operations to join the Transport Systems & Logistics Laboratory, part of the Centre for Transport Studies, in the Department of Civil & Environmental Engineering at Imperial College London.


This is an exciting opportunity to build theoretical and practical experience in the cutting edge of autonomous vehicle operations, with particular emphasis in multi-vehicle control and infrastructure design aspects. The post is linked to a project that will develop control algorithms that ensure the safe and efficient operations of autonomous vehicles in urban environments. Emphasis will be placed on modelling of the interactions between vehicles (automated and conventional) other road users with an emphasis on the automated identification of safety edge-cases.


As a member of the Transport Systems & Logistics Laboratory (led by Dr Panagiotis Angeloudis), the successful candidate will be joining a team of 14 researchers, with significant expertise in transport systems, autonomy, simulation, mathematical optimisation and machine learning. They will also be working closely with researchers at the Personal Robotics Laboratory (Department of Electrical & Environmental Engineering), the Institute of Security Science and Technology, our industrial partners and Transport for London.


This is a fixed term appointment up to 31st of March 2022 in the first instance.

 

Duties and responsibilities

The postholder will contribute to the development of large-scale traffic models using agent-based and traffic simulation platforms. These will be used to simulate V2X communications and develop centralised controller within simulated environments, considering the effects of potential failures of V2X communications (signal loss, transmission error or cyber-attacks).

Essential requirements


  • Practical experience in a broad range of techniques including machine learning, optimisation and simulation

  • Knowledge of Programming Languages (C++/C#, Python or equivalent)

  • Knowledge of Mathematical Methods for the modelling of traffic or pedestrian flows

  • Practical experience within a research environment and / or publication in relevant and refereed journals

  • Excellent written communication skills and the ability to write clearly and succinctly for publication

Further information

For informal enquiries about the post please contact Dr Panagiotis Angeloudis at p.angeloudis@imperial.ac.uk.

Our preferred method of application is online via our website. Please click ‘apply’ below or go to https://www.imperial.ac.uk/job-applicants/ and search using reference number ENG01445. 

Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £35,477-£38,566 per annum.

Any queries regarding the application process should be directed to Briony Webb at b.webb@imperial.ac.uk.

For technical issues when applying online please email recruitment@imperial.ac.uk.

Closing Date: 29 November 2020.

 

 

Documents

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Additional information

Please note that job descriptions cannot be exhaustive and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.

All Imperial employees are expected to follow the 7 principles of Imperial Expectations: 

  • Champion a positive approach to change and opportunity
  • Communicate regularly and effectively within, and across, teams
  • Consider the thoughts and expectations of others
  • Deliver positive outcomes
  • Encourage inclusive participation and eliminate discrimination
  • Develop and grow skills and expertise
  • Work in a planned and managed way 

In addition to the above, employees are required to observe and comply with all College policies and regulations.

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