Job Description

We are seeking a highly motivated and skilled Research Intern to join our team and contribute to an exciting project focused on AI-driven sensing algorithms for next-generation wireless systems. As part of the Radio Systems Research Team, you will collaborate with experienced researchers at Bell Labs to develop and evaluate advanced AI-based sensing solutions. This internship provides a hands-on learning experience, allowing you to apply your knowledge and skills in a practical and innovative research environment.

• Develop AI/ML-based signal processing pipelines for sensing applications, tailoring them to specific scenarios.

• Build, train, and assess the performance of ML models for sensing tasks, using both simulated and real-world datasets.

• Implement sensing modules and experimentation scripts in Python, ensuring efficient and robust code.

• Analyze and benchmark algorithm performance, providing insights into the effectiveness of different approaches.

• Optimize models for runtime efficiency, scalability, and real-world deployment, considering practical constraints.

• Collaborate closely with senior researchers, contributing to algorithm design, experimentation, and evaluation processes.

• Document research findings, code, and experimental workflows, ensuring transparency and reproducibility.

• Stay updated with the latest advancements in AI/ML and wireless sensing, and contribute to knowledge sharing within the team.

• Engage in regular team meetings and discussions, providing valuable insights and contributing to a collaborative research environment.

You have:

• Enrolled in a Ph.D. or MS (Research) program, with a strong academic background in AI/ML, wireless communications, signal processing, and information theory.

• Hands-on experience with AI/ML programming in Python, demonstrating a solid understanding of machine learning concepts and their practical implementation.

• Availability for a 6-month internship commitment, allowing for dedicated and focused contribution to the project.

• Exposure to 5G PHY standards is preferred, providing a deeper understanding of wireless communication protocols.

• Experience working with practical wireless datasets is advantageous, as it enhances the ability to apply theoretical knowledge to real-world scenarios.

• Research experience at the intersection of AI/ML and sensing (radar or ISAC) is highly valued, indicating a strong alignment with the project's focus.

• Familiarity with experiment design for evaluating sensing system performance is beneficial, ensuring a systematic and effective approach to research.

• Some exposure to information-theoretic concepts relevant to wireless and sensing is preferred, providing a comprehensive understanding of the field.

It would be nice if you also have:

• Excellent communication and collaboration skills, enabling effective teamwork and knowledge sharing within the research team.

Advancing connectivity to secure a brighter world.

Nokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world.

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Our recruitment process

We act inclusively and respect the uniqueness of people. Our employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law. We are committed to a culture of inclusion built upon our core value of respect.

If you’re interested in this role but don’t meet every listed requirement, we still encourage you to apply. Unique backgrounds, perspectives, and experiences enrich our teams, and you may be just the right candidate for this or another opportunity.

The length of the recruitment process may vary depending on the specific role's requirements. We strive to ensure a smooth and inclusive experience for all candidates. Discover more about the recruitment process at Nokia