Research Intern

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

Candidate Requirements:

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