The Bosch Research and Technology Center North America — with offices in Pittsburgh, Pennsylvania, Sunnyvale, California, and Cambridge, Massachusetts — is part of the global Bosch Group (), a company with over 70 billion euro revenue, 400,000 people worldwide, a very diverse product portfolio, and a history of over 125 years. The Research and Technology Center North America (RTC-NA) is committed to providing technologies and system solutions for various Bosch business fields primarily in the areas of Robotics, Human Machine Interaction (HMI), Energy Technologies, Internet Technologies, Circuit Design, Semiconductors and Wireless, and MEMS Advanced Design.
The Robot Learning Lab at Bosch Research Pittsburgh invites knowledgeable research interns for investigations at the intersection of Robotics, Multimodal Machine Learning, Embodied AI, Computer Vision, and Natural Language Processing. We seek to tackle challenging robotics and automation problems, having large-scale industrial impact; we also seek to formulate these industrial problems as interesting and important scientific investigations—often leveraging open-source models, methods, benchmarks, and simulators—with the ultimate goal of deploying these systems to the real world, to augment or work alongside humans and other agents. Multiple members of the lab dual-affiliate with Carnegie Mellon University and, together with collaborators from the Robotics Institute and Language Technologies Institute, we continue to make several key developments in dexterous manipulation, interactive perception for mixed prehensile and non-prehensile manipulation tasks, cross-embodiment transfer learning, few-shot policy generalization through robot trajectory retrieval, unseen / open-vocabulary mobile manipulation, online policy adaptation and failure reasoning through agentic foundation model frameworks, and more.
We expect the intern to display independence and maturity as a researcher, using their experience to construct compelling problem statements, engage in rigorous literature reviews and analyses, design and execute experimental plans, and extract salient insights from the experimental results. To be successful, we expect candidates to have experience in dealing with challenging problems in transfer representation learning and robotics, including: (i) learning safe, robust, or generalizable robot state representations; (ii) designing useful regularization objectives, pretext tasks, or auxiliary objectives; (iii) adapting or transferring representations across different domains (e.g., different embodiments, environments, sim-to-real, tasks, etc.); (iv) dealing with the practicalities related to implementing neural policies, e.g., non-convex optimization “tricks” and multi-machine/multi-GPU parallelized training of large models; (v) conducting careful model performance characterization + error analyses, e.g., determining informative ablations and baselines, inspecting and visualizing learned representations, identifying dataset biases; (vi) using closed- and open-source Vision-Language foundation models, e.g., for perception, planning, world-modeling, progress-monitoring, control, etc.; (vii) fine-tuning foundation models on few-shot examples or large-scale datasets.
Finally, the intern will be expected to contribute to the preparation of industrial patents and to work with teammates to publish a high-quality research paper in a major conference venue.
Tasks
Required Qualification:
Other Requirements
Desired Qualification:
By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.
BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics)
The U.S. base salary range for this intern position is $30.00-$58.00 hourly. Within the range, individual pay is determined based on several factors, including, but not limited to, type of degree, work experience and job knowledge, complexity of the role, type of position, job location, etc. Your Hiring Manager can share more details about the specific salary range for this position during the interview process.
For more information on our culture and benefits, please visit:
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