About the role
Company Description We Are Bosch. At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our areas of activity are every bit as diverse as our outstanding Bosch teams around the world. Their creativity is the key to innovation through connected living, mobility, or industry. Let’s grow together, enjoy more, and inspire each other.  Work #LikeABosch  Reinvent yourself:  At Bosch, you will evolve. Discover new directions:  At Bosch, you will find your place. Balance your life:  At Bosch, your job matches your lifestyle. Celebrate success:  At Bosch, we celebrate you. Be yourself:  At Bosch, we value values.  Shape tomorrow:  At Bosch, you change lives. Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch. Job Description Develop state-of-the-art Radar AI solutions using combination of classical signal processing and machine/deep learning-based approaches. Research and develop memory-efficient radar models, radar representation learning, novel interior sensing tasks. Collaborate with other researchers to integrate radar AI modules into the prototype systems. Summarize research findings in high-quality paper and/or patent submissions. Qualifications Required Currently enrolled as PhD student in Computer Science, Electrical Engineering, or related fields. 2+ years programming experience, proficiency in PyTorch(Lightning), HuggingFace(transformers), hydra. Broad knowledge of machine- and deep-learning algorithms and principles and state-of-the-art methods. Preferred Experience using radar data in machine learning projects. Knowledge of digital signal processing principle and methods. Publication record in top machine learning and signal processing venues. Experience with HPC platforms and job managers (Slurm, IBM LSF). Additional Information All your information will be kept confidential according to EEO guidelines. Indefinite U.S. work authorized individuals only.  Future sponsorship for work authorization unavailable.