**Job Family:** Research & Predevelopment **Req ID:** 495940 **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? **Transform the everyday with us!** **Company Overview** 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. **This is aremote internship; however, for a more immersive experience, the role may alsobe completed onsite, if preferred, at our Princeton, NJ location. Theinternship is full-time and requires a minimum commitment of six months.** **Role Summary** In this internship, you will work on **quantum-inspired algorithms** with a strong focus on **optimization** , **machine learning** , and/or **advancedsolvers** 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 **classicalalgorithms** that run efficiently on today’s HPC and cloud platforms. Your work will contribute to next-generation industrial capabilities such as: + Large-scalecombinatorial and continuous optimization for engineering design, planning, andoperations + Machinelearning models enhanced by quantum-inspired representations or trainingstrategies + Fast,robust solvers for complex industrial problems arising in simulation, digitalengineering, 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. **Key Responsibilities** + Research,implement, and benchmark **quantum-inspired optimization algorithms** forindustrially relevant problems. + Developand evaluate **quantum-inspired machine learning methods** , such asalternative model representations, training strategies, or hybridoptimization–learning pipelines. + Designand implement **advanced solvers** for large-scale linear or nonlinear problemsarising in engineering and industrial applications. + Comparequantum-inspired approaches against state-of-the-art classical optimization andML methods on representative industrial use cases. + Prototypescalable implementations in Python and/or C++ suitable for HPC, GPU, or cloudenvironments. + Collaborateclosely with domain experts, simulation engineers, and software researchers toensure practical relevance and impact. + Documentmethods and results, present progress to the research team, and contribute topublications or internal technology transfer where appropriate. **Required Qualifications** + Currently,enrolled in a PhD’s program in Applied Mathematics, Computer Science,Engineering, Physics, Operations Research, or other STEM degree from an accrediteduniversity. + Strongbackground in **quantum computing concepts** (e.g., quantum annealing,tensor networks, Quantum‑inspired Monte Carlo, …), with emphasis on classicalor quantum-inspired implementations. + Backgroundin **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-onexperience with **Python** and scientific computing or ML frameworks (e.g.,PyTorch, JAX, NumPy/SciPy). + Proficientin English both written and verbal + Legallyauthorized to work in the United States without company sponsorship now or inthe future. **Preferred** + Experiencewith mathematical programming or large-scale numerical solvers. + Experiencewith **C++** , HPC, GPU computing, or parallel programming. + Familiarity with Linux-based development environments + Abilityto learn new mathematical, algorithmic, and software concepts quickly. + Stronganalytical and problem-solving skills. + Abilityto work effectively in an interdisciplinary research environment. + Strongcommunication skills (written and verbal). + Abilityto work independently, take initiative, and manage time effectively. + Mustbe located in the U.S. and legally authorized to work in the U.S. for theduration of the internship. **About Siemens:** We are a global technology company focused on industry, infrastructure, transport, and healthcare. From more resourceefficient factories, resilient supply chains, and smarter buildings and grids, to sustainable transportation as well as advanced healthcare, we create technology with purpose adding real value for customers. Learn more about Siemens here (https://www.siemens.com/global/en/company.html) . **Our Commitment to Equity and Inclusion in ourDiverse Global Workforce:** We value your unique identity and perspective. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society, while ensuring that we attract the best talent based on qualifications, skills, and experiences. We welcome you to bring your authentic self and transform the everyday with us. \#LI-JS \#LI-Remote $43-$47 **Organization:** Foundational Technologies **Job Type:** Full-time **Category:** Internal Services