peterjansen_cv6c_media_july2018

Postdoctoral Position Available

I have a position open for a postdoctoral scholar in my lab, primarily centered around a project in explanation-centered inference (more details below). Folks with interdisciplinary backgrounds (for example, but not limited to: cognitive science) are encouraged to apply — the most important qualifications are that you’re comfortable writing software, that you’re fascinated by the research problem, and that you feel you have tools in your toolbox (that you’ll enjoy expanding after joining the lab) to make significant progress on the task.

The start date is flexible, and we’ll review applications as they come in until the position is filled. If you have any questions, please feel free to get in touch: pajansen@email.arizona.edu

Postdoctoral Research Associate I
https://uacareers.com/postings/31213

Position Summary
The Cognitive Artificial Intelligence Laboratory ( http://www.cognitiveai.org ) in the School of Information at the University of Arizona invites applications for a Postdoctoral Research Associate for projects specializing in natural language processing and explanation-centered inference.

Natural language processing systems are steadily increasing performance on inference tasks like question answering, but few systems are able to provide explanations describing why their answers are correct. These explanations are critical in domains like science or medicine, where user trust is paramount and the cost of making errors is high. Our work has shown that one of the main barriers to increasing inference and explanation capability is the ability to combine information – for example, elementary science questions generally require combining between 6 and 12 different facts to answer and explain, but state-of-the-art systems generally struggle integrating more than two facts together. The successful candidate will combine novel methods in data collection, annotation, representation, and algorithmic development to exceed this limitation in combining information, and apply these methods to answering and explaining science questions.

A talk on our recent work in this area is available here: https://www.youtube.com/watch?v=EneqL2sr6cQ

Minimum Qualifications
– A Ph.D. in Computer Science, Information Science, Computational Linguistics, or a related field.
– Demonstrated interest in natural language processing or machine learning techniques.
– Excellent verbal and written communication skills

Duties and Responsibilities
– Engage in innovative natural language processing research
– Write and publish scientific articles describing methods and findings in high-quality venues (e.g. ACL, EMNLP, NAACL, etc.)
– Assist in mentoring graduate and undergraduate students, and the management of ongoing projects
– Support writing grant proposals for external funding opportunities
– Serve as a collaborative member of a team of interdisciplinary researchers

Preferred Qualifications
– Knowledge of computational approaches to semantic knowledge representation, graph-based inference, and/or rule-based systems
– Experience applying machine learning methods to question answering tasks
– Knowledge of or interest in graphical visualization and/or user interface design
– Strong scholarly writing skills and publication record

Full Posting/To Apply
https://uacareers.com/postings/31213

Contact Information for Candidates Questions
Peter Jansen ( pajansen@email.arizona.edu )

Other Information
Tucson has been rated “the most affordable large city in the U.S.” and was the first city in the US to be designated as a World City of Gastronomy by the United Nations Educational, Scientific, and Cultural Organization (UNESCO). With easy access to both a vibrant arts and culture scene and outdoor activities ranging from hiking to rock climbing to bird watching, Tucson offers a bit of something for everyone.

The University of Arizona is committed to meeting the needs of its multi-varied communities by recruiting diverse faculty, staff, and students. The University of Arizona is an EEO/AA-M/W/D/V Employer. As an equal opportunity and affirmative action employer, the University of Arizona recognizes the power of a diverse community and encourages applications from individuals with varied experiences, perspectives, and backgrounds.

Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; access to UA recreation and cultural activities; and more!

The University of Arizona has been listed by Forbes as one of America’s Best Employers in the United States and WorldatWork and the Arizona Department of Health Services have recognized us for our innovative work-life programs.

peterjansen_cv6c_media_july2018

AI2 Talk: What’s in an Explanation? Toward Explanation-centered Inference for Science Exams

I recently gave a talk at the Allen Institute for Artificial Intelligence (AI2) on my work in explanation-centered inference for solving standardized science exams. This talk is a good high-level introduction to three recent papers on understanding the kinds of knowledge and inference required to build explanations (COLING 2016), our work in building a very large corpus of semi-structured explanations (the largest I’m aware of) to help us learn how to combine large amounts of information for inference (LREC 2018), and examining this corpus for common explanatory patterns that would help us make the task of building new explanations easier (AKBC 2017).

We’re very excited about this new knowledge resource that’s been two years in the making, and it’s potential for exploring explanation-centered inference. The Worldtree corpus is available here, at the Explanation Bank!