Multi-modal Sensing AI Research Intern

Bosch Group • Pittsburgh, PA

9d

About The Position

The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania and Cambridge, Massachusetts is a part of the global Bosch Group, a company with over 90 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America provides technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence (for example, human-assisted AI, natural language processing, robotics, 3D perception, and AI platform), energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design. The Bosch Research and Technology Center in Pittsburgh, PA is focused on the research and development of cutting-edge AI and sensing technologies that will shape the future of the company's products. This position is part of an ambitious effort to design and develop intelligent multi-modal sensing at the intersection of deep learning and signal processing, with diverse application domains ranging from physical security to intelligent and connected vehicles.

Requirements

• 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.

Nice To Haves

• Experience using raw sensor data (eg. Radar, ultrasound, acoustic etc.) in machine learning projects.
• Knowledge of digital signal processing principle and methods, multimodal representation learning.
• Publication record in top machine learning and signal processing venues.
• Experience with HPC platforms and job managers (Slurm, IBM LSF).

Responsibilities

• Develop state-of-the-art multi-modal models for active (radar, ultrasound) and passive sensing (acoustic, vibration, EEG) use-cases using combination of classical signal processing and machine/deep learning-based approaches.
• Research and develop solutions for multi-modal representation learning and modality adaptation with paired / unpaired sensor data.
• Collaborate with other researchers to evaluate the developed model on downstream applications.
• Summarize research findings in high-quality paper and/or patent submissions.

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees