Robeauté develops a microrobotic platform designed to navigate within the brain, with potential applications including biopsies, targeted drug delivery and electrode placement.
The platform combines DOT, the microrobot; CAP, its launch and retrieval platform; and MOM, the software used to control DOT’s deployment.
Your project
How do material properties, manufacturing tolerances and operating conditions affect a microrobot’s mechanical and thermal behaviour?
Joining the R&D team, you will investigate DOT and its internal components through two distinct workstreams: thermal simulation and mechanical simulation. You will develop and assess numerical models, comparing predictions with experimental data to understand how temperatures evolve, how components respond to loads over their intended service life, and which parameters most influence their behaviour. Your findings will help inform practical design decisions.
Together with your supervisor, you will define focused studies based on project priorities, available models and experimental data, with a scope designed for meaningful investigations within six months.
Why join Robeauté
At the microscale, familiar mechanisms can behave in unexpected ways. Surface interactions such as friction and adhesion can become more important relative to gravity, creating modelling challenges that require experimental investigation.
This internship offers the opportunity to explore these effects while building hands-on simulation skills on a microrobot being developed for neurosurgery. With regular technical guidance and close collaboration with the R&D team, you will learn how engineering evidence supports medical device development.
As the core work progresses, you may also explore how simulation results can be used to develop reusable numerical assets, surrogate models and digital twins.
What you will do
Develop or improve thermal and mechanical models, explaining your assumptions, material properties and boundary conditions.
Contribute to temperature characterisation studies and experimental work, and compare simulation results with measurements.
Assess the strength and service life of selected components under relevant loading conditions, considering potential failure modes and model limitations.
Perform sensitivity analyses to investigate how tolerances and variations in material properties affect predicted behaviour.
Present your findings, uncertainties and recommendations to support R&D design decisions.
Produce clear verification documentation, reusable models and automated reporting workflows so the team can build on your work.
Possible extensions include surrogate models and AI-based digital twins informed by numerical simulations. These will be explored according to progress and project priorities
The current estimate is 60–80% simulation and 20–40% experimental work, with the balance adjusted to the selected studies.
What you will learn
You will develop greater autonomy in engineering problem-solving, using simulations to assess proof-of-concept solutions and support clear, evidence-based design decisions.
You will learn to justify modelling choices, interpret differences between simulations and measurements, and explain what a model can reliably tell an engineering team.
You will also gain experience documenting verification work within a Quality Assurance and Regulatory Affairs (QA/RA) framework for medical device development.
Requirements
About you
You are a Bac+4/5 engineering or Master’s student, including final-year students, with a background in mechanical engineering, mechatronics, physics, thermal engineering or a related field.
Essential foundations
Strong foundations in mechanics and electronics or physics.
Experience using CAD software such as Onshape, Fusion 360 or an equivalent tool requred
Python programming skills for data processing and analysis.
A rigorous approach to analysing results and questioning assumptions, with the ability to explain your methods and…