Deimos Space was created in 2001 with the goal of delivering high-tech systems and engineering solutions in the aerospace field. The company currently employs more than 200 engineers, and has become one of the key players in the European space sector.
DEIMOS is selecting one senior engineer to be integrated in the GNC/AOCS Competence Centre (CC) of the Flight Systems Business Unit, to support new growth areas in Guidance, Navigation, and Control (GNC), enabled by Artificial Intelligence (AI).
The chosen candidate will be in charge of exploiting state-of-the-art solutions based on AI (including Machine Learning (ML), Reinforcement Learning (RL), Q-learning, among others) with the purpose of improving GNC design and verification techniques, with emphasis on Control.
Moreover, the chosen candidate will be responsible for managing such a type of project, directly interfacing the several stakeholders, including universities and research institutes, private companies, and the European Space Agency (ESA).
Experience in the space sector is welcome but not necessary.
As a member of the GNC/AOCS CC, the engineer will work in a team of other experienced engineers across Europe (Portugal, Spain, UK, Romania). The work of the GNC/AOCS CC is oriented to the design, development, specification, and validation of autonomous systems, including GNC and AOCS systems, for a broad range of aerospace and aeronautical platforms. As a matter of reference, DEIMOS’ activities cover
- Satellite formation flying, rendezvous, in-orbit servicing (IOS) and active debris removal (ADR)
- Entry, descent, and landing on planets (Earth, Mars) & natural satellites
- Launch vehicles
- Earth observation, upstream (flight segment) and downstream
- Interplanetary exploration and navigation
- Unmanned autonomous vehicles (UAVs, UGVs)
- System and mission design
The following types of responsibilities are envisioned:
- Project Management of Control and AI activities, within the GNC/AOCS CC
- Technical Leadership of AI-based GNC (especially Control-related) activities (projects and proposals) within the Competence Centre
- Specification, design, implementation, and validation of GNC algorithms, to be applied to satellites, launchers, and re-entry vehicles, among others
- Development and implementation of AI-based algorithms for Control, as well as other domains, including planning and Failure Detection, Isolation, and Recovery (FDIR)
The activities involved may include:
- Model-based design and software implementation of AI-based GNC algorithms
- Mathematical modelling
- Specification and validation of AI-based GNC solutions
- Analysis and trade-off of different AI techniques and frameworks
- Analysis and trade-off of AI and non-AI GNC solutions
- Technical and project management
A recognized engineering degree (Mechanical, Aerospace, Electrical, Electronic) or a related degree (e.g., Physics, Maths)
Postgraduate studies (MSc or PhD) on engineering and providing a solid background in most of the following topics:
- Artificial intelligence (AI) techniques, including machine/reinforcement learning and deep learning (required)
- Classical and robust control techniques
- Optimal control techniques
- Adaptive control techniques and system identification
- Optimization techniques
- Atmospheric flight dynamics
Engineer with at least 4 years of experience in the practical application of the domains relevant to the post (relevant MSc & PhD studies would also be considered).
The position will be tailored to the level of experience and additional industrial experience would be viewed very positively.
The following capabilities are required for the post:
- Strong background in control and simulation of dynamic systems
- Strong background in AI, especially for Control applications
- Capacity to understand new concepts and apply them to engineering problems
- Good programming skills
- Experience with Matlab and Simulink
The following capabilities are desired for the post:
- Experience in atmospheric flight
- Solid theoretical background in GNC/AOCS
- Background on multivariable robust control
- Background on optimal and adaptive control
- Experience in failure detection, isolation, and recovery
- Background in design and verification of cyberphysical systems
Good level of English, spoken and written
- Capability to integrate in and work within a team
- Autonomy and self-development
- Responsibility towards the customer and colleagues<