Drexel University, Teachable AI Lab

Position ID:Drexel University-Teachable AI Lab-POSTDOCTAIL [#21436]
Position Title: POSTDOCTORAL RESEARCHER - TEACHABLE ARTIFICIAL INTELLIGENCE LAB
Position Type:Postdoctoral
Position Location:Philadelphia, Pennsylvania 19104, United States [map]
Subject Area: Informatics / Teachable Artificial Intelligence Lab
Appl Deadline:none (posted 2022/03/17)
Position Description:   Remote  

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About Drexel

Drexel is one of Philadelphia's top 10 private employers, a comprehensive global research university and a major engine for economic development in the region. With over 24,000 students, Drexel is one of America's 15 largest private universities. Drexel has committed to being the nation’s most civically engaged university, with community partnerships integrated into every aspect of service and academics.

Job Summary

Drexel University's College of Computing and Informatics is seeking applications for a Postdoctoral Researcher to work at the Teachable Artificial Intelligence Lab—or TAIL for short (https://tail.cci.drexel.edu). The TAIL mission to better understand how people teach and learn and to build machines that can teach and learn like people do. The lab engages in both use-inspired and fundamental research to achieve this mission. The postdoctoral researcher will conduct work in the areas of cognitive systems and interactive machine learning. The position will be supported by two projects associated with the Army Research Lab’s STRONG program (https://www.arl.army.mil/business/collaborative-alliances/current-cras/strong-cra/):

Human-Guided Machine Learning for Futuristic Human-Machine Teaming. On this three-year project, we aim to create interactive machine learning techniques that enable more effective teaming between humans and machines. To achieve this goal, our team will develop a set of asymmetric cooperative multiplayer games that can serve as a testbed for humans and AI agents to partner up to solve problems. On this effort, the Drexel researchers will lead the development of AI agents that can interact with humans in these games. In particular, the project will focus on developing teachable AI agents that can learn on the fly from natural interactions with their human partners while participating in cooperative problem solving. The project aims to develop agents that can interactively learn from multiple, mixed modalities, such as learning from a combination of demonstrations, feedback, and natural language instruction. Co-evolution of Human-AI Adaptation. On this three-year project (which is closely aligned to the previous project), our team will develop AI agents that leverage a technique called interactive task learning (see: https://web.eecs.umich.edu/~soar/sitemaker/docs/pubs/Laird_et_al_InteractiveTaskLearning_IEEE_IntelligentSystems_2017.pdf). This approach lets humans interactively teach an agent to perform novel tasks through natural language instruction. To evaluate our agents, human participants will team up with them to accomplish tasks in a virtual reality game environment—leveraging the AI agents as personal assistants to support problem solving and interactively teaching them new knowledge as needed. Across both projects, the postdoctoral researcher will support the development of AI agents that can learn interactively with/from human teammates across multiple asymmetric cooperative games. The project will be highly collaborative, with faculty and students from 6 different academic institutions collaborating to accomplish the project’s goals (Drexel University, Carnegie Mellon University, University of Colorado Boulder, University of Wisconsin-Madison, University of California—San Diego, and California State University—Long Beach).

Essential Functions

- Support development of AI agents that can learn interactively with/from human teammates in the context of multiple asymmetric cooperative games. - Discover new approaches that enable AI agents to more naturally and efficiently interact with and learn from human teammates. - Prepare and submit manuscripts to appropriate conferences/journals in the field. - Help manage and advise graduate and undergraduate students - Interact professionally with all members of the research team. Required Qualifications

A PhD (or anticipated PhD) in computer science, information science, human-computer interaction, or other related area.

Preferred Qualifications

Candidate should have a strong background in artificial intelligence, (AI) particularly in areas such as cognitive systems, cognitive architectures, knowledge-based AI, and interactive task learning.

Additional Information

We are seeking candidates for a one-year appointment (potentially renewable for the duration of the project, up to 3 years total), with the possibility of remote work.

This position is classified as exempt with a salary grade of I. For more information regarding Drexel’s Professional Staff salary structure, https://drexel.edu/hr/career/ducomp/salstructure/

All applicants must apply through Drexel Careers: http://careers.drexel.edu/cw/en-us/job/497801. For more information about to the position, please contact Chris MacLellan (christopher.maclellan@drexel.edu).


We are not accepting applications for this job through AcademicJobsOnline.Org right now. Please apply at http://careers.drexel.edu/cw/en-us/job/497801 .
Contact: Chris MacLellan
Email: email
Postal Mail:
3675 Market Street
Philadelphia, PA 19104
Web Page: http://careers.drexel.edu/cw/en-us/job/497801