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Internal Research Fellow (PostDoc) in Artificial Intelligence

Posted 24 Mar 2024
Work experience
3 to 5 years
Full-time / part-time
Full-time
Job function
Degree level
Required language
English (Fluent)

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Our team and mission

The Software Systems Division deals with development techniques for ground and space systems. This covers all life-cycle aspects from requirements specification to development, verification, validation and maintenance. The role of the Division’s Software Technology Section is to explore the use of new technologies. A particular focus is the use of artificial intelligence techniques in space software applications.

This area includes several technology areas, e.g.:

  • Machine learning (ML) techniques for verification, validation and maintenance, based on the analysis of data captured during verification and validation tests and spacecraft operations.
  • Planning techniques to increase the on-board autonomy of spacecraft, in particular in telecommunication and Earth observation constellation missions.
  • Model-based system/software engineering to support the development of AI applications and improve the existing tools and methods by using artificial intelligence techniques.
  • Optimisation of artificial intelligence techniques in order to facilitate their execution on board spacecraft.

As Research Fellow, you will work in a team of experienced engineers in the domain of space software and AI. You will be able to interface with experts from other engineering disciplines for applications and potential demonstrations. You will be responsible for:

  • providing AI/ML expertise for the development of AI/ML systems and their applications (command and control, AOCS and GNC, etc.), whether supporting ESA missions and projects, ESA R&D activities, or ESA working groups on AI/ML;
  • supporting the elaboration of an AI/ML strategy for use in space systems and processes, together with an associated roadmap and risks;
  • disseminating results of technical reporting through peer-reviewed journal publications, colloquiums and webinars;
  • prototype applications, proof of concepts and related tests in the Departmental laboratory facilities to assess technologies developed. This can e.g. be in the areas of mission management, AOCS and GNC algorithms;
  • contributing to the development of advanced benchmark problems that can serve as baseline and reference cases for various R&D projects.

You are encouraged to visit the ESA website: https://www.esa.int/

Field(s) of activity/research for the traineeship

In line with the application areas and technology domains, you will be assigned to consolidating research and applying AI technology for one of the following topics. The specific topic(s) will be detailed and consolidated in line with the your profile and experience.

Machine learning - preventive maintenance and improved mission management and control:

For this topic, the objective of the project is to study the state of the art of machine learning and data mining algorithms that would make it possible to detect anomalies in the data recorded during the verification and validation of space systems as well as during space system operations. The anomalies to be detected include regressions with respect to the previous execution of tests, sporadic behaviour and the identification of trends that could lead to anomalies, through automatic and exhaustive analysis of test results and environment data. All spacecraft systems, including attitude control algorithms, are candidates for this anomaly detection process.

Planning and autonomy: autonomous operations:

For this topic, the objective of the project is to study the state of the art of planning algorithms that would support on-board autonomous operations of a space systems. This could be a telecommunication or Earth observation constellation. Autonomy concepts will be implemented on board one of the constellation spacecraft in order to manage high-level requests (objectives and constraints) sent from the ground and ensure the mission’s highest availability (telecommunication) and greater responsiveness (Earth observation). Similarly it could be applied to orbital robotics and satellite systems (like active debris removal, exploration, space transportation systems).

Model-based system/software engineering: artificial intelligence applications:

For this topic, the objective of the project is to study the state of the art of model-based system/software engineering techniques and tools, focusing on two aspects. The first is adaptation of these techniques to support the development and integration of AI applications in space systems. The second aspect is to identify and develop tools or add-ons to the existing tools that can support the development of system/software (e.g., model verification, code verification, test generation, etc.).

Optimisation: optimisation of models, improvement of performance: Some artificial intelligence techniques require a large amount of memory and high-performance processors. For this topic, the objective of the project is to study and evaluate the different techniques that can be used to ensure the correct execution of AI techniques with minimal resources and an increase in performance through specific libraries (e.g., OpenCV, SIMD) or generation of an optimised compiler (e.g. XLA).

Technical competencies

  • Knowledge relevant to the field of research
  • Research/publication record
  • Ability to conduct research autonomously
  • Breadth of exposure coming from past and/or current research/activities
  • Ability to gather and share relevant information
  • General interest in space and space research

Behavioural competencies

  • Result Orientation
  • Operational Efficiency
  • Fostering Cooperation
  • Relationship Management
  • Continuous Improvement
  • Forward Thinking

Education

You should have recently completed, or be close to completion of a PhD in a related technical or scientific discipline. Preference will be given to applications submitted by candidates within five years of receiving their PhD.

Additional requirements

The ideal candidate for the position would have:

  • a theoretical (academic) background in AI,
  • a systems standpoint,
  • a pragmatic approach

This position, located at the crossroads of academic approaches and industrial applications, of AI and software systems engineering, is at the core of current embedded systems challenges. It is also an opportunity to transition gradually from an academic context to an industrial perspective.

You should have good interpersonal and communication skills, to interact with the systems engineering AI and MBSE community, and be able to work in a multicultural environment, both independently and as part of a team. Good methodological and organisational skills are required.

You should demonstrate an interest in space as well as the ability and interest to get actively involved in prospective interdisciplinary research.

The working languages of the Agency are English and French. A good knowledge of one of these is required. Knowledge of another Member State language would be an asset.

The European Space Agency (ESA) is Europe’s gateway to space. Its mission is to shape the development of Europe’s space capability and ensure that investment in space continues to deliver benefits to the citizens of Europe and the world.

Aerospace & Defence
Noordwijk
4,000 employees