Postdoctoral Research Fellow in Intelligent Navigation for Space Vehicles

City, University of London

Postdoctorate Position Fixed Term London, UK

Uploaded 12 Nov 2020

Job Description

Context 

Developments adopting Artificial Intelligence (AI) for navigation, more precisely for space navigation, are very innovative. More importantly, the application of the latest deep neural network technology to this field is of ultimate novelty. The potential for applicability of AI spans multiple space scenarios and missions, such as like LIDAR-based precise planetary landing missions or camera-based orbital relative navigation. For this, the strategy is to build a deep, full navigation algorithm including the imaging processing part and the relative motion estimation part that are required to achieve accurate Guidance, Navigation and Control (GNC) operations, integrated together. We will work on this topic for multiple scenario cases with the prestigious body European Space Agency (ESA) and the qualified person will have the chance to interact ESA technical officers.

Job Purpose

The Postdoctoral Research Fellow involved in this project will focus on the study and preliminary development of deep learning-based networks for algorithms required to achieve accurate LIDAR space landing and vision-based orbital rendezvous scenarios. The developed algorithms are required to be tested in simulation, tested at City, University of London facilities and at ESA ESTEC facilities in the Netherlands.

Main Responsibilities 

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

  • Undertake research in the field specified to meet the aims, objectives and project specifications given in the proposal.
  • Build upon previous literature and experience in Space Robotics, Navigation and Localisation, in relation to space landing and orbital space rendezvous.
  • Support the administration of the project including preparation and maintenance of Risk Assessment procedures and forms, as well as study monitoring, etc.
  • Preliminary design and development of the algorithms of the project.
  • Work with the project consortium to improve and test the algorithms developed.
  • Liaise with other members of the research team to ensure the delivery of the project objectives and achievement of milestones.
  • Contribute to reporting of the progress of the research.
  • Take an active role in IP protection, including drafting patents.•Prepare and make presentations on the work for the project requirements.
  • Work as a member of the research team within the discipline, playing a full part in the research life of the University in general, and the School of Mathematics, Computer Science and Engineering, in particular.
  • Take up other duties and tasks, such as supporting the writing of research and teaching activities, as may reasonably be assigned by the supervisor and/or Head of School.

Salary

The salient features of conditions of service for Research and Analogous staff are as follows:

  • Salary will be within the range of £38,017 to £44,045 per annum on Grade 6 of the salary scales for Research and Analogous staff.
  • Annual Leave is 30 days, plus 8 statutory and 4 additional days during the Christmas holiday period.
  • Automatic entry into the Universities Superannuation Scheme (USS) with the option to opt out.
  • This post is permanent with fixed-term funding for 12 months.
  • This post is full time (1.0 FTE).•All offers of appointment are subject to City receiving satisfactory references and medical clearance.
  • All posts at City are subject to reasonable adjustment under the Equalities Act (2010).
  • All appointments at City are subject to a probationary period.
  • The appointment is terminable by three months’ notice on either side.

Applications

When preparing your application, you should address carefully the post details enclosed and in particular the qualities outlined in the Person Specification. Please include examples where appropriate. All applications must be received by the advertised deadline.

Person Specification

The successful candidate will hold a relevant PhD in Electrical or Mechanical Engineering, Space Engineering, Computer Science, Mechanical Engineering or a related field. They should have experience in research in the area of space engineering, deep networks, guidance navigation and control and computer vision. Software and Real time programming capabilities is highly desirable.

Essential

  • A relevant PhD in Electrical Engineering, Space Engineering, Computer Science, Mechanical Engineering, or a related field.
  • Capability to carry out advanced research in the area of AI and Deep Networks, Space Engineering, Navigation and Control.
  • Experience of processing of data and presenting results in a suitable format for dissemination of results in journals or at conferences,etc.
  • Can work well within a team of researchers and play a full part in the work of SMCSE.
  • Demonstrate a strong desire to be successful in achieving the aims and objectives of the proposal.
  • Demonstrate the ability to meet deadlines and work under tight time scales.
  • Show excellent verbal and written communication skills including presentation and report-writing.
  • Demonstrate excellent interpersonal skills and the ability to liaisewith colleagues, industrial partners, and other external contacts.
  • Demonstrate the ability to work effectively with IT tools, manipulate, sort, and correctly interpret data and to present them effectively in a variety of ways.

Desirable

  • Experience in Space Rendezvous applications.
  • Experience in Space Landers.
  • Experience in designing Deep Networksfor classification and regression.
  • Experience in Navigation (Localisation) through vision-based motion estimation.
  • Experience of research project administration
  • Experience of research dissemination.
  • Experience with Software and Real time Programming and Hardware Validation.