Multi-Modal Cyber-Physical Sensing Intern

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.

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 70 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 (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design.

Job Description

Bosch Research and Technology in Pittsburgh is seeking a motivated student intern to join our research team exploring advanced machine learning applications in IoT and smart home systems. This position is part of an exciting effort to explore intelligent multi-modal sensing at the intersection of deep learning and signal processing, with projects spanning smart home automation, connected appliances, and innovative ways to enhance everyday user experiences. You will contribute to building, testing, and refining machine learning models for sensor data analysis and work alongside experienced researchers to translate innovative ideas into practical applications.

Responsibilities:

• Assist in research and development of multi-sensor data fusion techniques using data such as acoustic, vibration, radar, lidar, image, Wi-Fi, time series, and ultrasound signals.
• Support the design, training, and evaluation of multi-modal machine learning models for smart home, IoT, or manufacturing use cases.
• Collaborate with cross-functional teams to help prototype and test new sensing solutions.
• Document and communicate research findings clearly, contributing to internal reports, presentations, and potential publications or patents.
• Stay up-to-date with emerging technologies and assist in exploring novel applications for IoT and smart home systems.

Benefits:

• Hands-on experience with cutting-edge multi-sensor and machine learning research.
• Mentorship from experienced researchers in IoT, home appliances, and cyber-physical systems.
• Opportunity to contribute to real-world projects with potential impact on products and processes.

Qualifications

Qualifications

Required:

• Currently pursuing a PhD in Computer Science, Electrical Engineering, Data Science, or a related technical field.
• ?Broad knowledge of machine- and deep-learning algorithms and principles and state-of-the-art methods.
• Familiarity with sensors, IoT devices, or cyber-physical systems is a plus.
• Proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow.
• Strong communication skills and an ability to work collaboratively in a research environment.
• Enthusiasm for learning and applying new technologies.
• Minimum GPA of 3.0

Desired:

• Experience using raw sensor data (eg. Radar, 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 additional programming languages (C, C++) or embedded systems.
• Interest in computer systems, networking, or signal processing.

Additional Information

Equal Opportunity Employer, including disability / veterans.

Please note that employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.