AI Research Intern - Hybrid AI for Intelligent Assistance

Job Description:

Job Description

(COMPANY NAME) Research Pittsburgh would like to invite an enthusiastic research intern for investigations at the intersection of Knowledge Representation and Reasoning, Machine Learning, and Natural Language Processing. We wish to develop algorithms for context understanding on the basis of heterogeneous information, spanning from textual resources (e.g., Q/A datasets, FAQ, emails, manuals, crowd-sourced annotations) to sensor-based data (e.g., streamed from smart devices of different type). We wish to integrate such algorithms to human-machine-interaction interfaces, with specific interest in conversational AI.

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: semantic web technologies, with a focus on knowledge graphs and knowledge graph embeddings; machine learning, including traditional approaches and more recent deep neural methods (with a focus on language models); crowd-based solutions, including human-in-the loop approaches. Regardless of the method(s), the intern must understand the relevant challenges of developing a neuro-symbolic AI architecture.

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 in a major conference (AAAI, ECAI, ISWC, ESWC, IJCAI, LREC, ACL, NAACL, EMNLP, etc.)
Tasks
* Perform extensive state of the art review
* Generate a research plan, detailing intended approaches and evaluation methods
* Implement, apply and evaluate neuro-symbolic algorithms for relevant downstream tasks
* Present related work and research progress to colleagues, on a weekly basis
* Formalize findings as contribution to patent filing (if applicable)
* Summarize findings as a research paper (required)

Qualifications

* Strong background in AI, including symbolic and sub-symbolic approaches
* Experience with Semantic Web technologies (e.g., Apache Jena, Stardog) and standards (e.g., RDF, OWL, SPARQL)
* Experience with data analytics toolkits, such as scikit-learn, MATLAB, or R
* Experience in deep learning model development, using PyTorch
* Experience with NLP toolkits (e.g., Stanford Core NLP, NLTK, GATE)
* (Preferred) Familiarity with frame-based semantics, computational lexical resources

Additional Information

Other Requirements
* Degree Level: doctoral or post-doctoral
* Major: Computer Science (or related)

Logistics
* 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.
(COMPANY NAME) 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)

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