Connectionists: Funded PhD position (University of Strathclyde, Glasgow, UK)

[Annalisa Riccardi]

PhD position in Deep Learning & Knowledge Management for Spacecraft Design

Fully funded PhD position available at the Department of Mechanical and Aerospace Engineering of the University of Strathclyde (Scotland, UK) in collaboration with the European Space Agency (Netherlands),  Airbus Defence and Space (Germany) and RHEA Group (Belgium).

Project Start Date: between November 2017 and February 2018.
Supervisors: Dr Annalisa Riccardi

Details:  The proposed research is aimed at developing a database of knowledge and lessons learned from the design of space systems by making use of modern techniques such as Natural Language Processing, Deep Learning and Deep relational networks. To build these kind of databases and networks usually a very lengthy process of interviews and manual collection and organisation of data is required. The proposed research project aims to automatically infer this knowledge from existing datasets of components and/or mission studies reports as well as freely available online resources.

The project is a first step towards the development of a Design Engineering Assistant (DEA). The DEA, will provide support to the engineer for quick assessment studies, and running in the background will provide real-time feedback to the actions taken by the spacecraft designer. The intelligent agent is not intended to replace the human in the design process but rather to enhance his perception of the problem and possible solutions through the quickly evaluations of different alternatives.

The enrolled student will have the opportunity to collaborate on a complimentary project with another PhD candidate at the European Space Agency.

Eligibility: A first Class or Upper Second Honours degree (or equivalent overseas qualification) in an appropriate discipline (e.g., computer science, applied mathematics or aerospace/electronics and electrical engineering). You should be able to demonstrate excellent mathematical, analytical and programming skills. Previous experience in machine/deep learning and database management would be advantageous.

Funding: This project is fully funded by the University of Strathclyde through the Research Excellence Award scholarship.

The studentship covers the University tuition fees (at EU/UK level) and provides an annual tax free stipend (rate for 2017-2018 is £14,553 p.a. tax-free) and appropriate bench fees.  NB it will not cover the overseas tuition fees for students who are outside of the EU.

The student will be part of the Intelligent Computational Laboratory (ICE Lab, www.icelab.uk<http://www.icelab.uk>) of the Aerospace Centre of Excellence of the Mechanical and Aerospace Engineering Department of the University of Strathclyde, Glasgow, UK.

In the first instance, interested parties should contact (with their CV) the supervisor: annalisa.riccardi at strath.ac.uk

Best regards,

Annalisa Riccardi, PhD
Lecturer, Chancellor’s Fellow

ICE Lab
the Intelligent Computational Engineering Laboratory
www.icelab.uk
info at icelab.uk
________________________________________
Aerospace Centre of Excellence
Department of Mechanical & Aerospace Engineering
Strathclyde University
James Weir Building, 75 Montrose Street
G1 1XJ Glasgow
+44.141574.5169