Research Fellow in AI and Autonomous Systems

City, University of London
June 19, 2024
Offerd Salary:£41,732
Working address:N/A
Contract Type:Other
Working Time:Full time
Working type:N/A
Ref info:N/A

Job number


School / Service

 School of Science & Technology


 Department of Engineering


 Tait Building

Contract type


Job category




Salary min


Salary max


Publication date


Closing date


Founded in 1894, City, University of London is a global university committed to academic excellence with a focus on business and the professions and an enviable central London location.

City attracts around 20,000 students (over 40% postgraduate level) from more than 150 countries and staff from over 75 countries.

In the last decade, City has almost tripled the proportion of its total academic staff producing world-leading or internationally excellent research. During this period, City has made significant investments in its academic staff, its estate and its infrastructure and continues to work towards realizing its vision of being a leading global university.

The culture at City is built on our shared core values, which means that all employees are expected to behave according to our values: “We care, We learn, We act.”


Robotics, Autonomy and Machine Intelligence (RAMI) Grouphttps: // www.

The Robotics, Autonomy and Machine Intelligence (RAMI) Group led by Prof Nabil Aouf is dedicated to fulfil customer's ambitious and innovative requirements.


The key tasks of the appointee to this research are to:

  • Undertake research in the field of AI, vision based GNC of autonomous vehicles (Space, Drones and ground vehciles)
  • Undertake research from algorithm development to real time implementation.
  • Prepare, publish, and present papers and presentations on the related work for highly ranked Journals and major meetings and Conferences, as specified by the Principal Investigator.
  • Person Specification

    A PhD (obtained or nearly finishing it) in Engineering (Electrical/Mechanical/Aeronautical) or Computer Science


  • Capability to carry out research on one or more of the following areas: Autonomous Vehicles, AI and Deep Learning, Vision based GNC, Robotics, Computer vision, Embedded and Realtime Systems
  • Knowledge of Vehicles dynamics and modeling
  • Experience of processing of data and presenting results in a suitable format for dissemination of results in reports presentations, and research papers etc.
  • Skills and Abilities

  • Demonstrable knowledge of Programming skills (Python/C++/Matlab)
  • Interest in developing AI and deep learning based solutions
  • An ability to work effectively with research staff, students and customers
  • An ability and willingness to learn new technical skills
  • Demonstrate the ability to meet deadlines and work under tight time scales
  • Demonstrate excellent verbal and written communication skills
  • Additional Information

    City offers a sector-leading salary, pension scheme and benefits including a comprehensive package of staff training and development.

    Closing date: 19th June 2024 at 11:59pm.

    Interviews are scheduled for WC 24th June.

    To apply and for more information about the post please use the links below.

    For an informal discussion please contact Nabil Aouf via [email protected]

    Where hybrid working can be accommodated, specific arrangements will be agreed with the successful candidate before their start date. Regardless of where colleagues are working, City, University of London's premises will be their primary and contractual place of work.

    City, University of London is committed to promoting equality, diversity and inclusion in all its activities, processes, and culture for our whole community, including staff, students and visitors.

    We welcome applications regardless of age, caring responsibilities, disability, gender identity, gender reassignment, marital status, nationality, pregnancy, race and ethnic origin, religion and belief, sex, sexual orientation and socio-economic background.

    City operates a guaranteed interview scheme for disabled applicants.

    The University of business, practice and the professions.

    Available documents
  • SST00221 JD.pdf
  • From this employer

    Recent blogs

    Recent news