Robot Learning Research Intern
Robot Learning Research Intern
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Job Description
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 largescale industrial impact; we also seek to formulate these industrial problems as interesting and important scientific investigationsoften leveraging opensource models methods benchmarks and simulatorswith 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 dualaffiliate 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 nonprehensile manipulation tasks crossembodiment transfer learning fewshot policy generalization through robot trajectory retrieval unseen / openvocabulary 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 simtoreal tasks etc.); (iv) dealing with the practicalities related to implementing neural policies e.g. nonconvex optimization tricks and multimachine/multiGPU 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 opensource VisionLanguage foundation models e.g. for perception planning worldmodeling progressmonitoring control etc.; (vii) finetuning foundation models on fewshot examples or largescale datasets.
Finally the intern will be expected to contribute to the preparation of industrial patents and to work with teammates to publish a highquality research paper in a major conference venue.
Tasks
- Discuss relevant tasks in Robotics / Embodied AI and quickly agree on research topic
- Perform extensive literature review to understand the current stateoftheart methods
- Generate an R&D plandetailing the relevant research questions selected AI/ML task(s) intended methodology experiments evaluation metrics and publication venue targets
- Maintain an ongoing report of progress towards goals and present related literature and project status to supervisor(s) and/or colleagues on a weekly basis
- Design and implement proposed methodology according to the above research plan while remaining aware of any new developments in the field
- Perform extensive evaluation of the proposed approach and generate results (e.g. proofs quantitative results that compare the main results with baselines and ablations qualitative analysis that visualizations the behavioral tendencies of the approach)
- Work with supervisor(s) to publish a highquality research paper in a major conference venue e.g. NeurIPS ICML ICLR CoRL RSS CVPR/ICCV/ECCV ICRA IROS etc.
Qualifications :
Required Qualification:
- Strong background in ML with emphasis on multimodality and/or representation learning
- Strong background in Robot Learning Robotics or Embodied AI
- Extensive experience in fromscratch neural model implementation
- Extensive experience with data analytics toolkits such as numpy pandas and scikitlearn
- Extensive experience in implementing training/finetuning and evaluating the performance of CV models NLP models RL/IL policies etc.
- Extensive experience in leveraging Large Language Models VisionLanguage Models and/or foundation models that are grounded with other modalities (e.g. audio haptics etc.)
- Extensive experience in training neural models on multimachine or multiGPU setups
- Extensive experience in working on robot hardware platforms
- Extensive publication history in top conference venues; is a mature researcher
Other Requirements
- Your degree level: pursuing doctoral degree or recent postdoctoral researcher
- Your major: Robotics Machine Learning Computer Engineering or related
Desired Qualification:
- (Preferred) Extensive experience in development in Python on Linuxbased systems
- (Preferred) Theoretical background in ML topics e.g. transfer representation learning nonconvex optimization reinforcement learning provably safe learning etc.
Additional Information :
By choice we are committed to a diverse workforce EOE/Protected Veteran/Disabled.
BOSCH is a proud supporter of STEM (Science Technology Engineering & Mathematics)
- FIRST Robotics (For Inspiration and Recognition of Science and Technology)
- AWIM (A World In Motion)
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:
Culture and Benefits Bosch in the USA
Remote Work :
No
Employment Type :
Intern
Employment Type
Intern
