Internship: Machine Learning in Radar Sensing for ADAS

Key Skills

Effective communication skills, MATLAB Programming, Python Programming

Job Description

Your Team

We are a research group within the Radio Frequency Processing business that works on long-term innovation topics like automotive radar, connectivity and health IoT. We are currently looking for a graduate student (9-month thesis/12-month towards a thesis + internship) to shape these future topics.

Project description

Radar is a core perception technology in advanced driver assisted systems (ADAS) for enhancing safety and convenience. Future radar systems in vehicles will likely move to the higher millimeter-wave bands and incorporate more digital processing and machine learning capabilities. These developments open up new opportunities for radar-based sensing and perception. We have multiple topics around the use of machine learning (ML) techniques in radar sensing for ADAS and in-cabin monitoring. Some projects are on exploring new machine learning schemes like reinforcement learning to explore the interplay between radar sensing, perception and ADAS controls; detection of data anomalies in radar ML and the design of robust ML methods; radar data emulation methods for ML.

What’s in it for you

• A great opportunity to develop your skills (technical, soft skills, communication, etc.)
• Gaining experience in a multinational and diverse environment
• Possibility to become part of NXP’s Young Professional Talent Pool
• Working on industrial research assignments which contribute to NXP’s goals

Your profile

• Enrolled as a Master’s student in computer/electrical/electronic engineering, or a relevant field of study.
• Background in signal processing and machine learning.
• Prior knowledge of radar systems (via coursework or projects) is a plus.
• Experience in Matlab/Python scripting.
• Strong oral and written communication skills in English.
• Strong motivation in working in an R&D environment.

Duration 

This is a full-time internship (40 hours per week) with a duration of 9 months or longer. The assignment could also be suitable as a thesis/graduation project. The start date of this project is in September 2023.

Please note that in order to be considered for an internship/working student assignment, you need to be registered as a student during the entire period.