Open Source Hardware enthusiasts — I am an artificial intelligence professor/researcher, and have more work this year than there are hours in the day. This is greatly reducing my free time, and ability to contribute to open source hardware, such as this project. I’m looking for a postdoctoral scholar interested in joining my lab at the University of Arizona, who is interested in the artificial intelligence of language and inference, to work on some exciting research projects, and help reduce some of my work load. Please forward this advertisement to anyone you feel may be interested. I would like to find someone as soon as possible.
Postdoctoral Position Available in Natural Language Processing
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: firstname.lastname@example.org
Postdoctoral Research Associate I
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
– A Ph.D. in Computer Science, Information Science, Computational Linguistics, or a related field.
– Demonstrated interest in natural language processing, machine learning, or related 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 (One or more of the following would be a strong benefit — note not required for application)
– 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
Contact Information for Candidates Questions
Peter Jansen ( email@example.com )
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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!
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