PhD Opportunities at SET
PhD opportunities within the Space and Exploration Technology group are in the Systems, Power & Energy and Autonomous Systems and Connectivity Research Divisions. If you are interested in any of these projects, you should email the prospective supervisor for discussing your intentions.
The James Watt School of Engineering has a limited number of scholarships to offer to excellent candidates, application shall be discussed with the potential supervisor. A call for scholarship applications is open, with deadline 31 January 2026.
See currently-available opportunities of Scholarships on our our Postgraduate Research.
PhD topics
Multidisciplinary space mission design using machine learning
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
The design and optimisation of a mission trajectory is usually the first stage in a space exploration mission; nevertheless, trajectory design depends on some knowledge of certain propulsion system characteristics that are usually unknown in the early design stages. For example, techniques to design and optimise for low-thrust solar-electric propulsion are fundamentally different to those used for high-thrust chimical engines. Even within one propulsion technology, the estimation of the trajectory cost and time of flight depends on engine data such as maximum thrust, specific impulse, and others. Ideally, an holistic mission design process, that optimises simultaneously the trajectory and the propulsion system specifications, would allow to achieve an optimal design point at once, without the need of multiple iterations.
While this could be achieved with traditional multidisciplinary optimisation, this PhD will explore the use of machine learning, to achieve design optimality. Some early research has shown that this can be done for a limited set of parameters and a limited design space: this PhD will greatly extend these preliminary findings, to develop a tool that can be used for a wide range of mission scenarios, from small propelled satellites to long and expensive interplanetary missions.
Background in orbital dynamics, space mission design, machine learning are desired.
Quantum computing for space trajectory design and optimisation
Supervisors
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
Quantum computing one of the most important emerging technologies: a step change in our ability to solve difficult problems, in the same way conventional computers have been in the sixties. Conventional computers rely on bits, which can carry on/off information; quantum computers use quantum bits, or “qubits”, which can represent several states at once, exploiting the superposition effect of quantum theory. This allows them to work much faster than conventional computers, and adding more qubits make quantum computers exponentially faster, allowing them to solve problems that are so difficult that are out of reach for ordinary calculators.
In the space mission design, the trajectory design problem is a difficult one, even more so when multiple bodies and/or targets have to be selected from a set (e.g. multiple planetary swing-bys, multiple moon or asteroid tours, multiple satellite servicing and/or disposal): this creates a mixed combinatorial-continuous problem, where the combinatorial part is (broadly speaking) a variant of the classic Travelling Salesperson Problem (TSP), to select the sequence of bodies/targets, and in order to evaluate each sequence, a continuous optimisation sub-problem is to be solved. Quantum computing has the potential to dramatically improve the solution of this problem, my exploiting the superimposition of multiple possible paths at once.
As progress is being made into the hardware to make functional quantum computers, scaling up the number of qubits, this PhD will explore the formulation and solution of space mission design problems through a quantum computing. We aim to answer the following research questions:
- What quantum computing framework(s) can be used for space mission trajectory design?
- How can we leverage on and inject quantum computing to the space mission trajectory design problem, particularly when multiple bodies/targets are involved?
- How can trajectory design problems be encoded through a quantum algorithm?
- To what extent a full trajectory design problem can be implemented as (and take benefit from) a quantum algorithm?
Ultimately, we will assess to what extent, injecting quantum computing into the optimisation problem, we obtain a quantum advantage, both in terms of optimality of solution, and computational cost, for this specific application (narrow advantage).
The ideal candidate will have a background in computing science or similar discipline, with a strong interest in space technology and exploration, or vice-versa a background in space trajectory design with strong interest in computing science and programming.
In-orbit assembly: Robust autonomous methods for controlling robot manipulators in space
Supervisors
Dr Gerardo Aragon Camarasa (School of Computing Science)
Funding
Currently unfunded. Please consult the Postgraduate Research section for information on applying for support.
Description
With the current push towards space for both private and government organizations, and the recent increase on initiatives to the industrialization of space, there will be an important need for humans to be supported by robotic systems. Understanding and mastering the unique properties that will intervene in the robot behaviour is essential to offer a fully autonomous robotic system which will be expected to work with no human intervention while being robust, accurate and responsive.
The work will consider the different advantages of both traditional and AI-based control methodologies to support the development of a vision-based control system that is able to control a robot manipulator within the space environment during in-orbit assembly tasks. The expected outcome of this work will be a simulation environment of a suitable setup and a practical real-life implementation.
This project will engage with recent research studies on the field on autonomous robotics, building in-orbit structures, satellite assembly and support studies on manufacturing in space. This project can also engage with users beyond space, with advanced manufacturing research being a potential area to explore.
Background in either control engineering mechatronics, computing science, and/or space engineering is highly recommended. In order to be eligible to apply for the School of Engineering Scholarship, an excellent CV is required.
RESEARCH LINES
This project explores the following lines of research:
- Robotic arms for manufacturing in space
This line of research focuses on the analysis of the dynamics, kinematics, and grasping methodologies of the robotic arms while on orbit. This addresses problems related to autonomous robotics, target capture strategy, tackling a moving orbiting object, mathematical approach to the robotic arm dynamics, and contact forces. In addition, the major physical interactions while executing tasks on orbit such as building in-orbit structures, satellite assembly, and space manufacturing, will be considered.
- Approaches for controlling robotic manipulators in space
This line of research focuses on the analysis and exploration of traditional and AI-based control methodologies, intelligent control algorithms, and an integrated vision-based control system. This addresses problems related to the vision system embedded in the robot, environment simulation, and parameters such as speed, torque, vibration, and attitude disturbance.