Research Engineer (Structural/Finite Element Analysis for Maritime Drone Operations)

This role focuses on developing and executing finite element analysis (FEA) simulations of drone-vessel impacts in maritime environments, estimating structural damage to critical vessel subsystems, and translating simulation outputs into damage severity classifications and risk matrices. The engineer will also develop surrogate models to accelerate damage predictions and integrate results into the project's separation-assurance framework and Maritime Digital Twin. The role involves working with PhD students, researchers, vessel operators, and collaborators to support system integration, testing, and validation.

Responsibilities

• Develop finite element analysis (FEA) frameworks to estimate structural damage from multirotor drone-vessel collisions in maritime environments.
• Formulate impact analysis problems, including drone impact trajectories, weight classes, vessel component geometry and material properties, and structural damage severity classification.
• Develop and execute nonlinear/explicit dynamic FEA simulations (e.g., ANSYS, Abaqus) covering mid-flight and landing-phase crash scenarios on different vessel types.
• Develop methods to translate structural damage severity into functional-impact and risk classifications for critical vessel subsystems.
• Develop data-driven or physics-informed surrogate models trained on FEA outputs to accelerate damage-severity prediction, reducing reliance on repeated simulations.
• Integrate damage estimation outputs with crash-area prediction and separation-assurance models within the project’s overall risk framework and the Maritime Digital Twin.
• Identify and prioritise critical versus non-critical vessel components and zones, working with vessel operators and the classification society to obtain relevant structural data.
• Design and conduct simulation experiments, sensitivity analyses, and validation studies to evaluate damage estimation accuracy, robustness, and generalisation across vessel types.
• Work with PhD students, research fellows, vessel operators, drone operators, and project collaborators to support system integration, testing, validation, and demonstration.
• Prepare technical reports, research publications, presentations, project deliverables, and documentation for stakeholder and expert review.

Requirements

• Bachelor’s or Master’s degree in Aerospace Engineering, Mechanical Engineering, Material Science and Engineering, Civil/Structural Engineering, or a closely related discipline.
• Strong academic or project background in finite element analysis, structural mechanics, or impact/crash simulation.
• Strong communication and problem-solving skills.
• Strong sense of ownership, responsibility, and initiative.
• Ability to work effectively with researchers, engineers, students, industry partners, and project stakeholders.
• Willingness to support project reporting and milestone reviews.
• Demonstrated hands-on experience with FEA software, specifically nonlinear or explicit dynamic solvers used for impact/crash simulation (e.g., Abaqus Explicit, LS-DYNA, or ANSYS Explicit Dynamics).
• Competent in structural mechanics, material behaviour under dynamic/impact loading, and failure/damage modelling.
• Scripting ability (e.g., Python) for simulation automation, post-processing, or coupling FEA outputs with downstream risk models.
• Experience integrating simulation, damage/risk assessment, and reporting workflows within a research or engineering project framework.
• Ability to scope, build, and validate simulation models independently from limited or partial input data.
• Ability to work across structural engineering, impact mechanics, and maritime domains.
• Ability to deliver research outcomes within project timelines and contribute to high-quality publications.

Nice to have

• Research or project experience in maritime/naval structures, impact studies, or structural damage assessment would be advantageous.
• Familiarity with drone dynamics or aerospace impact studies would be advantageous.
• Experience translating engineering simulation results into risk matrices or decision-support outputs for non-specialist stakeholders would be beneficial.
• Programming skills in Python or MATLAB for simulation data processing and analysis would be an advantage.
• Familiarity with surrogate modelling and physics-informed neural networks (PINNs) for generalising simulation-based predictions would be an advantage.