Job Description

Bosch Research Pittsburgh would like to invite an enthusiastic and knowledgeable research intern for investigations at the intersection of Knowledge Representation and Reasoning, Machine Learning, and Natural Language Processing. We wish to develop algorithms for making-sense of heterogeneous information, spanning from textual resources (e.g., FAQ, emails, manuals, crowdsourced annotations) to sensor-based data (e.g., streamed by smart environments, wearables, autonomous vehicles). We wish to integrate such algorithms to an open source chatbot interface, enabling decision support in the Information Space through basic Q/A interactions.

We expect the intern to perform implementation and evaluation of various methods, inspired by his/her own insights, team discussion, and contemporary academic literature. Viable methods may comprise: machine learning, including traditional approaches and more recent deep neural methods, semantic web technologies, crowd-based intelligence. Regardless of the method(s), the intern must understand the relevant challenges of developing a hybrid architecture that leverages symbolic and sub-symbolic approaches to Artificial Intelligence (AI).

Together with our faculty collaborators in the Language Technologies Institute (LTI), in the School of Computer Science at Carnegie Mellon University (CMU), we have made several key developments that we expect the prospective intern to leverage and extend. The final, key component of the internship is scientific contribution; the prospective intern is expected to work with teammates to publish a high-quality research paper.

Tasks

• Perform extensive literature review, to understand the current state-of-the art
•  Generate a research plan, detailing intended approaches and evaluation methods
• Present related work and research progress to colleagues, on a weekly basis
• Implement (and evaluate) algorithms for reasoning over heterogeneous information
•  Integrate algorithms with off-the-shelf chatbot platforms (e.g., Dialogflow, MS Bot, etc.)
• Formalize findings as contribution to patent filing (if applicable)
• Summarize findings as a research paper

Qualifications

• Strong background in AI, including symbolic and sub-symbolic approaches
• Experience with data analytics toolkits, such as scikit-learn, MATLAB, or R
• Experience in deep learning model development, using PyTorch
• Familiarity with NLP tools (e.g., Stanford Core NLP, NLTK, GATE)
• (Preferred) Experience with Semantic Web technologies (Apache Jena, Stardog, etc.)
• (Preferred) Existing publication history in top conference venues (e.g., IJCAI, AAAI, LREC, ISWC, ESWC, NIPS, ICML, ICLR, CVPR, ACL, NAACL, EMNLP)

OTHER REQUIREMENTS

• Degree Level: doctoral or post-doctoral
• Major: Computer Science (or related)

Additional Information

• Location: Pittsburgh, Pennsylvania, United States
• Start date: Typically, between April and June
• Duration: Typically, 14 weeks (extension possible; subsequent research collaboration encouraged)

By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.

BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics) Initiatives

• FIRST Robotics (For Inspiration and Recognition of Science and Technology)
• AWIM (A World in Motion)