Research Fellow in AI and Autonomous Systems

Job number

 SST00221

School / Service

 School of Science & Technology

Department

 Department of Engineering

Location

 Tait Building

Contract type

 Fixed-term

Job category

 Research

Hours

 Full-time

Salary min

 £41,732

Salary max

 £41,732

Publication date

 03-Jun-2024

Closing date

 19-Jun-2024

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.”

Background

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

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

Responsibilities

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

Experience

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