Number of Positions: 3
Duration: 10 Weeks
Date: June 1st to August 7th, 2026

Location: On-site, Murray Hill, NJ.

Educational Recommendations

Currently a candidate for a Ph.D. program in Physics, Electrical Engineering, Materials Science, Nanotechnology, Chemical Engineering, Chemistry, Computer Science, Data Science, Biomedical Engineering, Biochemistry, or a related field with an accredited school in the USA.

Based on the specific project, you must have:

• Experience in condensed matter physics, 2D quantum system simulations, and low-temperature experimental techniques.
• Solid foundation in electromagnetism, RF engineering, and low-noise electronics.
• Experience with AI/ML techniques for communication, sensing, localization, image processing, or biomedical imaging.
• Programming skills in MATLAB and/or Python.
• Familiarity with biosensing, biomaterials, and medical imaging technologies.

It would be nice if you also had:

• Hands-on experience with data acquisition, nanofabrication, and prototyping for RF, optical, or quantum systems.
• Strong analytical skills in data analysis and visualization to interpret experimental results and optimize device performance.

You will collaborate with multidisciplinary teams and contribute to technical publications and patents advancing Nokia’s leadership in emerging technologies. You will contribute to pioneering research in one of multiple cutting-edge areas, helping shape the future of sensing, communication, and computing. Your work may include:

• Topological Quantum Computing: Support the development of topological qubits through research in device simulation, nano-fabrication, and/or low-temperature transport measurements of our highly-stable Ga As quantum platform.
• Quantum RF Sensing: Explore quantum-enabled RF technologies for ultra-sensitive detection and next-generation communication systems through modeling, prototyping, and experimental validation.
• Low-Power Radio Networks: Design and evaluate new wireless communication approaches such as backscatter and wake-up radio systems for AI-enabled sensing and localization.
• Biomedical Sensing with AI/ML: Develop algorithms for signal processing, image reconstruction, and extraction of quantitative biomarkers from multimodal optical imaging data (e.g. OCT) and implement predictive AI/ML models that enable real-time assessment and decision support in wound-healing applications.