Research Scientist - Multi-modal Sensing AI

Robert Bosch•Pittsburgh, PA

55d

About The Position

Originating from Bosch AI research in Pittsburgh, we are responsible for pushing the boundaries of signal sensing and multimodal models through key innovations to solve complex industry problems and shape the future of Bosch products and services for both internal and external users. We work with internal partners of different Bosch business units to transfer our solutions into future products. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals. In this position, you are expected to: Develop and lead research projects focusing on multi-sensor data fusion, including acoustic, vibration, radar, lidar, image, Wi-Fi, time series, and ultrasound data, to improve sensing capabilities in autonomous driving vehicles, predictive maintenance in manufacturing processes, and next generation smart home devices, leading to enhanced safety, efficiency, and user experience. Design, build, train, evaluate multi-modal deep-learning models that leverage sensor signals, and work together with several business units within Bosch to transfer research artifacts into products and processes. Offer expert insights to the management team in relevant technology sectors, aiding in strategic planning, R&D trajectory, and investment decisions. Stay abreast of the latest technological innovations, document and disseminate research findings through high-caliber publications and/or patent submissions.

Requirements

Ph.D. in Computer Science, Electrical Engineering, Information Technology or a related discipline
In-depth experience in signal processing for sensor data and their integration with deep-learning methods.
Proficiency in Python, PyTorch (including libraries such as torchaudio, torchvision, torchmetrics), familiarity with PyTorch Lightning.
A strong publication record in relevant venues such as ICASSP, InterSpeech, WASPAA, SenSys, IPSN, ICCPS, ICML, ICLR, ICRA, CVPR, ICCV, ECCV, NeurIPS, or equivalent contributions to the field such as patents or significant open-source projects.
Strong interpersonal, communication, and teamwork capabilities.

Nice To Haves

3+ years of experience in industrial research.
Proficiency with version control systems (Git), integrated development environment (VSCode or PyCharm) and experience with experiment tracking tools (MLFlow).
Familiarity with high-performance computing (HPC) systems and job schedulers (Slurm, LSF).
Hands-on experience in product development in the above-mentioned areas for consumer/enterprise markets.
Experience leading projects with small teams, demonstrating the ability to mentor junior researchers and interns, manage project timelines, and deliver results within time constraints.

Responsibilities

Develop and lead research projects focusing on multi-sensor data fusion, including acoustic, vibration, radar, lidar, image, Wi-Fi, time series, and ultrasound data, to improve sensing capabilities in autonomous driving vehicles, predictive maintenance in manufacturing processes, and next generation smart home devices, leading to enhanced safety, efficiency, and user experience.
Design, build, train, evaluate multi-modal deep-learning models that leverage sensor signals, and work together with several business units within Bosch to transfer research artifacts into products and processes.
Offer expert insights to the management team in relevant technology sectors, aiding in strategic planning, R&D trajectory, and investment decisions.
Stay abreast of the latest technological innovations, document and disseminate research findings through high-caliber publications and/or patent submissions.

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