
Operations Research Scientist
4 weeks ago
We are seeking a Operations Research Scientist to champion the full lifecycle of engineering-scale optimization solutions. You will translate real-world engineering challenges into robust mathematical models, implement high-performance algorithms and deliver production-grade applications that drive measurable improvements across aerospace and adjacent sectors. The successful candidate will drive customer-facing deployments, deliver technical presentations, and contribute to advanced simulation campaigns in MATLAB/Simulink, Python and C++.
Key Responsibilities
- Formulate and refine large-scale optimization problems (LP, IP, MIP, NLP, QP) to address engineering use cases such as structural sizing, trajectory planning and flow control.
- Implement and benchmark different optimization methods, gradient-based solvers, metaheuristics and quantum-inspired routines—in MATLAB/Simulink, Python and C++.
- Embed BQPhy optimization engines into aerospace simulations, such as hypersonic flow, structural sizing, trajectory planning, systems models, digital mission planning and dynamic modelling.
- Work closely with systems engineers, simulation specialists and product teams to translate technical requirements into mathematical formulations and software deliverables.
- Design representative test cases, run benchmark simulations and validate results against empirical or high-fidelity data.
- Remain current with advances in mathematical optimization and numerical methods; incorporate emerging techniques to enhance solution capability.
Required Qualifications
- Master's or PhD in Applied Mathematics, Optimization, Computational Science, Aerospace Engineering or equivalent discipline
- 1–3 years' experience developing and deploying engineering-scale optimization algorithms preferred; strong academic or research experience also acceptable and fresh graduates are encouraged to apply.
- Exceptional customer-facing skills: articulate communicator, adept at technical presentations
- Proficiency with optimization solvers (Gurobi, CPLEX or equivalent), MATLAB/Simulink, Python and C++; strong command of numerical libraries and version control (Git).
- Demonstrable expertise in aerospace simulation methodologies.
- Advanced mathematical and algorithmic problem-solving aptitude.
- Willingness to undertake domestic and international travel as project requirements dictate.
Preferred Qualifications
- Practical experience with CFD tools (e.g. Fluent, FUN3D, StarCCM+) and FEA tools (e.g. ABAQUS, ANSYS Mechanical, OptiStruct)
- Proven track record of delivering complex solutions within multidisciplinary teams
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