Quantum- Algorithms Industrial Researcher Internship

Quantum-inspired Algorithms for Industrial Applications Researcher Internship

Here at Siemens, we take pride in enabling sustainable progress through technology. We do this through empowering customers by combining the real and digital worlds. Improving how we live, work, and move today and for the next generation! We know that the only way a business thrives is if our people are thriving. That’s why we always put our people first.

Our global, diverse team would be happy to support you and challenge you to grow in new ways. Who knows where our shared journey will take you?

Siemens Foundational Technology (FT) is the central R&D organization of Siemens, shaping the future of industrial technologies through advanced algorithms, optimization, and AI. Our mission is to accelerate innovation across Siemens’ industry, infrastructure, mobility, and energy businesses by translating cutting‑edge computational methods into practical, scalable industrial solutions.

We are looking for a highly motivated intern to join our Simulation Research Group in Princeton, NJ. The team develops next‑generation algorithmic methods that bridge advanced mathematics, computer science, and real‑world industrial applications.

Transform the everyday with us!

In this internship, you will work on quantum‑inspired algorithms with a strong focus on optimization, machine learning, and/or advanced solvers for industrial‑scale problems. Rather than targeting quantum hardware, the emphasis is on leveraging ideas from quantum computing (e.g. annealing‑inspired methods, tensor representations, and probabilistic formulations) to develop classical algorithms that run efficiently on today’s HPC and cloud platforms.

Your work will contribute to next‑generation industrial capabilities such as:

• Large‑scale combinatorial and continuous optimization for engineering design, planning, and operations
• Machine learning models enhanced by quantum‑inspired representations or training strategies
• Fast, robust solvers for complex industrial problems arising in simulation, digital engineering, and decision‑making

You will be mentored by experienced researchers and collaborate in an interdisciplinary environment spanning applied mathematics, optimization, machine learning, simulation, and industrial application domains.

• Research, implement, and benchmark quantum‑inspired optimization algorithms for industrially relevant problems
• Develop and evaluate quantum‑inspired machine learning methods, such as alternative model representations, training strategies, or hybrid optimization‑learning pipelines
• Design and implement advanced solvers for large‑scale linear or nonlinear problems arising in engineering and industrial applications
• Compare quantum‑inspired approaches against state‑of‑the‑art classical optimization and ML methods on representative industrial use cases
• Prototype scalable implementations in Python and/or C++ suitable for HPC, GPU, or cloud environments
• Collaborate closely with domain experts, simulation engineers, and software researchers to ensure practical relevance and impact
• Document methods and results, present progress to the research team, and contribute to publications or internal technology transfer where appropriate

• Currently enrolled in a PhD program in Applied Mathematics, Computer Science, Engineering, Physics, Operations Research, or other STEM degree from an accredited university
• Strong background in quantum computing concepts (e.g. quantum annealing, tensor networks, Quantum‑inspired Monte Carlo, …), with emphasis on classical or quantum‑inspired implementations
• Background in optimization (e.g. annealing, gradient‑descent), machine learning (e.g. dimensionality reduction, inference, high‑dimensional data representation), or numerical methods (e.g. linear solvers, differential equation solvers, root finding)
• Hands‑on experience with Python and scientific computing or ML frameworks (e.g., PyTorch, JAX, Num Py/Sci Py)
• Proficient in English both written and verbal
• Legally authorized to work in the United States without company sponsorship now or in the future

• Experience…