Robotics Engineer (Multi-body Dynamics)

Company Description Cosmoserve Space is dedicated to building a cleaner and more sustainable future for space exploration through advanced active debris removal technologies. The company focuses on high-tech, cost-effective solutions that address the growing challenge of space debris and help safeguard the orbital environment. With a team of passionate experts and a strong engineering culture, Cosmoserve Space is at the forefront of responsible and next-generation space activities. Team members work on impactful projects that ensure the cosmos remains accessible and safe for future missions. Applicants can expect a mission-driven environment that values innovation, collaboration, and technical excellence.
ABOUT THE ROLE
Cosmoserve Space is developing precision robotic systems for space-adjacent environments where dynamic accuracy is mission-critical. As a Robotics Engineer specialising in Multi-body Dynamics (MBD), your primary focus is building, simulating, and validating high-fidelity models of complex robotic systems — capturing joint interactions, contact forces, flexible structures, and actuation behaviour across an entire mechanism. You will work with industry-leading MBD tools and develop simulation environments from the ground up. Dedicated Controls Engineers own the controller design, and Software Engineers handle large-scale software development; your role is to produce the accurate dynamic models and simulation outputs they both depend on.
KEY RESPONSIBILITIES
Multi-body Modelling
• Develop high-fidelity multi-body dynamic models of robotic systems including manipulators, deployable structures, and contact-rich mechanisms using MuJoCo, Adams, Simscape Multibody, or equivalent MBD tools.
• Define and parameterise joint types, constraint equations, mass/inertia properties, and actuation models to accurately represent physical hardware.
• Model flexible body effects, structural compliance, and backlash where relevant to system performance.
• Conduct system identification experiments on real hardware and tune MBD models to match measured dynamics.
Simulation & Analysis
• Set up and run forward dynamics, inverse dynamics, and quasi-static simulations to analyse robot behaviour across operating conditions.
• Perform contact and collision simulations — including soft contact, friction, and impact — using MuJoCo and complementary tools.
• Carry out parametric studies, sensitivity analyses, and Monte Carlo simulations to characterise system robustness and performance envelopes.
• Integrate MBD models with ROS/ROS 2 pipelines to enable hardware-in-the-loop (HIL) and software-in-the-loop (SIL) testing.
Collaboration & Documentation
• Hand off validated dynamic models and simulation results to the dedicated Controls Engineering team, providing the parameter sets and behavioural data they need to design and tune controllers.
• Work with the Software Engineering team to expose simulation environments and model interfaces through ROS/ROS 2, scripting lightweight Python or MATLAB wrappers as needed — without owning the larger software codebase.
• Model straightforward mechanical parts and assemblies in CAD; extract inertial properties and build simulation-ready URDF or Adams representations from these models.
• Maintain clear model documentation, version-controlled simulation environments, and reproducible experiment workflows.
• Contribute to technical reports, design reviews, and — where applicable — external publications or conference papers.
REQUIRED SKILLS
MBD Simulation: MuJoCo (primary), MSC Adams, Simscape Multibody, Issac Sim
Robotics Middleware: ROS / ROS 2, URDF / XACRO, Gazebo, RViz
Scripting & Analysis: Python (working proficiency), MATLAB / Simulink, Git — for model scripting, data analysis, and automation (large-scale software development handled by Software Engineers)
Dynamics & Mechanics: Rigid body dynamics, Lagrangian & Newton-Euler formulations, Contact mechanics, Flexible body modelling
Control Fundamentals: Working understanding of PID, computed torque, and MPC — sufficient to interpret controller requirements and produce relevant simulation outputs for the Controls team
Math Foundation
Linear algebra, Differential equations, Lie groups / SO(3), SE(3), Numerical integration methods
CAD Modelling
SolidWorks — part modelling and assembly (non-complex geometry), mass/inertia extraction, STEP / STL to URDF or Adams pipeline
Analysis & Validation
System identification, Parametric studies, HIL / SIL testing, Data analysis (NumPy, pandas, MATLAB)
NICE TO HAVE
• Experience with NVIDIA Isaac Sim or GPU-accelerated physics simulation environments.
• Familiarity with flexible multibody dynamics (FEM coupling, Abaqus or ANSYS co-simulation).
• Knowledge of space mechanisms — deployable booms, solar array drives, robotic arms for on-orbit servicing.
• Background in sim-to-real transfer techniques and domain randomisation for MBD models.
• Prior publication, thesis, or project demonstrating MBD modelling of a complex robotic system.
QUALIFICATIONS
• B.Tech / M.Tech in Mechanical Engineering, Robotics, Aerospace Engineering, or a closely related field.
• 2–3 years of hands-on experience with multi-body dynamics simulation in a robotics, aerospace, or mechanical systems context.
• Demonstrated proficiency with MuJoCo and at least one additional MBD platform (Adams, Simscape Multibody, PyBullet, or Webots).
• Solid theoretical grounding in Lagrangian mechanics, Newton-Euler dynamics, and constraint-based formulations.
• Ability to script and automate simulation workflows in Python or MATLAB; large-scale software development is not required.
• CAD proficiency in SolidWorks or Fusion 360 — able to independently model straightforward parts and assemblies (non-complex geometry) and prepare them for simulation import, including inertia extraction and joint definitions.
• Comfortable working alongside dedicated Controls and Software Engineering teams, providing simulation outputs and model interfaces rather than owning those domains.
• Strong numerical skills and comfort working with large, multi-variable dynamic systems.

Work arrangement
No