Computational Optimization Research Intern

About BQP

BQP is building the next-generation simulation platform, BQPhy® , designed to solve the most complex computational challenges in aerospace, space, and defense. The platform integrates advanced solvers with proprietary quantum-inspired algorithms, delivering performance beyond the capabilities of modern GPUs. Running on classical high-performance computing systems, BQPhy® has demonstrated up to 10X computational advantages for aerospace and defense clients. The platform is built to transition seamlessly to quantum-native hardware as it matures, enabling sustained technical superiority and reduced development costs across industries.

About this Role

We are advancing the future of space technologies by integrating cutting-edge optimization techniques into real-world aerospace applications. From trajectory design and satellite constellation management to design optimization of space systems, our team focuses on solving some of the most challenging problems in the industry.

We are looking for a motivated Optimization Applications Intern who is passionate about applying mathematical optimization, algorithms, and computational intelligence to space-related problems.

Intern Profile and Required Competencies

• Support the development and testing of optimization models for space industry applications (e.G., trajectory planning, satellite scheduling, structural design, resource allocation).
• Implement and benchmark algorithms (classical optimization, evolutionary algorithms, metaheuristics, or mathematical programming).
• Contribute to simulation studies and analyze trade-offs in multi-objective optimization problems.
• Work with datasets from aerospace systems to validate and refine models.
• Strong foundation in optimization techniques (linear, nonlinear, integer programming, evolutionary algorithms, or heuristics).
• Programming proficiency in Python (experience with libraries such as Pyomo, CXYPY, SciPy, DEAP, or OR-Tools ), MATLAB and C++.
• Solid mathematical background (operations research, multi-objective optimization, numerical methods).
• Strong analytical and problem-solving skills.
• Collaborate with the R&D team to explore novel approaches (e.G., quantum-inspired optimization).
• Document research findings and present results to technical and non-technical stakeholders.