Deep Learning and Knowledge Management for Spacecraft DesignPhD 3 years Glasgow, UK
The design of complex systems necessitates the use of increasingly intelligent algorithms to support the "human-in-the-loop". The proposed research is a first step towards the development of a Design Engineering Assistant (DEA) that will leverage the latest techniques in machine learning, data mining and knowledge management to support future space mission designs
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/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.
Qualifications: Applicants require to hold a Masters degree in computer science, applied mathematics or aerospace/electronics and electrical engineering
Experience: experience in the field of machine learning, deep learning and database management is desirable.
The deadline for this position has passed
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