Internal Research Fellow (PostDoc) in Applied Optimisation Techniques under Uncertainty

Our team and mission

You will be part of the Mission Analysis Section in the Flight Dynamics Division at the European Space Operations Centre (ESOC). This Division is a centre of technical excellence, responsible for the development, implementation and operations in the domain for ESA missions throughout the Solar System. ESOC is responsible for spacecraft operations for ESA missions, including the development of ground systems for operations and operations preparations.

You will work closely with colleagues in multiple domains, including Mission Analysis and the Space Debris Office. Our mission is to establish common solutions to challenges faced by users throughout the Agency.

You are encouraged to visit the ESA website: www.esa.int
www.esa.int/About_Us/ESOC https://download.esa.int/esoc/esa_ESOC_BR_web_2015.pdf

Field(s) of activity/research for the traineeship

This research aims to develop techniques for optimisation under uncertainty that ESA can adopt in important mission scenarios.
Optimisation under uncertainty is a mathematical and computational approach used in decision-making. It is employed to find solutions that are not only optimal under expected or average conditions but also remain satisfactory or feasible when facing variations or uncertainties in the underlying parameters.
The primary objective is to account for the inherent uncertainties in the system and design a solution that can perform well across a range of scenarios, rather than just optimising the performance for a single deterministic scenario. This makes the techniques particularly valuable in situations where uncontrollable or unpredictable factors can potentially affect the system's performance.
Currently, when planning complex missions with challenging manoeuvres, such as multiple chaser collision avoidances, in-orbit servicing, post-launch eclipse avoidance, close flybys, or orbit insertions around Solar System bodies, deterministic techniques are used to optimise the spacecraft's trajectory, creating a reference or planned path. However, the trajectory of the spacecraft or Solar System bodies is uncertain due to estimation processes relying on noisy data. Conducting manoeuvres introduces additional uncertainty into the system. A robust manoeuvre strategy is one that acknowledges these uncertainties and permits the specification of stochastic constraints on trajectory design. For instance, instead of avoiding collisions or eclipses deterministically, these techniques enable the setting of constraints, such as ensuring that the probability of a collision or eclipse remains below a threshold value.
When implementing automated systems, for example for coordinating space traffic or performing automated cislunar transfer, such techniques might be considered mandatory.
In recent years, various techniques have emerged in astrodynamics, such as stochastic optimisation, robust optimisation, reinforcement learning, and polynomial optimisation using differential algebra. These methods have been applied in scientific literature and recent studies, including projects conducted by NASA-JPL in mission analysis at ESOC.
As a research fellow in this domain, you will explore these techniques further and refine them for practical use in operational scenarios. This research's main objective is to facilitate the transition from theoretical studies to real-world mission scenarios, enabling robust optimisation techniques in challenging or automated mission scenarios.

Technical competencies

Behavioural competencies

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

For more information, please refer to ESA Core Behavioural Competencies guidebook

Education

You should have recently completed or be close to completion of a PhD in optimisation or a related field. Preference will be given to applications submitted by candidates who have received their PhD within the past five years.

Additional requirements

In addition to your CV and your motivation letter, please prepare a research proposal of no more than 5 pages. This proposal should be uploaded to the "additional documents" field of the "application information" section.

You should have:

• deep knowledge of the subject area, optimisation under uncertainty;
• strong software development skills in Python and C++;
• experience with modern software development environments, GitLab, CI/CD;
• experience with astrodynamics, orbital theory and spacecraft mission design.

You should also have good interpersonal and communication skills and should be able to work in a multi-cultural environment, both independently and as part of a team. Your motivation, overall professional perspective and career goals will also be explored during the later stages of the selection process.

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.