URL for this advertisement: <http://tiny.cc/postdocs> http://tiny.cc/ut-postdoc
------------------------------ Prof. Matt Lease <http://www.ischool.utexas.edu/~ml> is seeking a Postdoctoral Research Fellow to join his research lab <http://ir.ischool.utexas.edu/> at the University of Texas at Austin (UT Austin), USA. Applications will be reviewed as they are received, and the position will remain open until filled. Work Location. The candidate is expected to relocate to Austin, TX <https://www.ischool.utexas.edu/about/about-austin> (USA) for this position. Innovation and research come to life in Austin, known for its mix of culture and technology. Duration and Compensation. This postdoctoral position, with flexible start date, provides an initial year of support that is renewable for up to two additional years. Typically postdocs remain for multiple years unless they obtain a faculty position sooner. The salary will be $60,000 per year, plus a standard package of benefits. Responsibilities. The Fellow will be expected to pursue individual research and collaborative research projects: designing studies, collecting and analyzing data, disseminating findings, mentoring student researchers, attending regular meetings, and performing project administration. This position will be a 40 hour/week research appointment, with no obligation to teach, although teaching opportunities may be available if desired. About the Research. Our research spans Human Computation and crowdsourcing, Information Retrieval (IR), and Natural Language Processing (NLP). Our lab does both back-end artificial intelligence (AI) modeling and front-end human-computer interaction (HCI). We build and test predictive models, design ways to better annotate labeled data, and explore human-in-the-loop approaches for human-AI teaming. We think about building fair and transparent AI: e.g., how to build explainable AI systems that facilitate effective human-AI teaming, and how to annotate data in ways that mitigate AI bias. We conduct fundamental research and apply it to real-world problems, such as fighting fake news <https://sites.google.com/view/ut-misinformation-ai/> and hate speech. See our recent publications <https://www.ischool.utexas.edu/~ml/publications/> and talks <https://youtube.com/playlist?list=PLV4pUk6bTwEYCy8w_syoVFL-gYd6s4frL> in top conferences such as AAAI, ACL, AIES, CHI, CSCW, HCOMP, KDD, NeurIPS, and the Web Conference. Example research includes: - Annotation agreement and aggregation: WebConf’20 <https://www.ischool.utexas.edu/~ml/papers/braylan_web2020.pdf>, KDD’21 <https://utexas.box.com/v/braylan-kdd21>, WebConf’22 <https://utexas.box.com/v/braylan-webconf22> - Crowdsourcing task design: JAIR’20 <https://www.ischool.utexas.edu/~ml/papers/kutlu_jair20.pdf> (award), CSCW’21 <https://dl.acm.org/doi/10.1145/3476073ible-gold-can-help>, Frontiers’22 <https://www.frontiersin.org/articles/10.3389/frai.2022.828187/full> - Explainable fact-checking: AAAI’18 <https://www.ischool.utexas.edu/~ml/papers/nguyen-aaai18.pdf>, UIST’18 <https://www.ischool.utexas.edu/~ml/papers/nguyen-uist18.pdf>, CHIIR’22 <https://utexas.box.com/v/shi-chiir2022>, ACL’22 <http://x> - Hate speech detection: NeurIPS’21 <https://utexas.box.com/v/rahman-neurips21>, iConference’22 <https://utexas.box.com/v/prateek-iconf22> - Human-AI teaming: AIES’21 <https://dl.acm.org/doi/abs/10.1145/3461702.3462516>, ICJAI’21 <https://utexas.box.com/v/gao-ijcai2021> - Information Retrieval Evaluation: CIKM’18 <https://www.ischool.utexas.edu/~ml/papers/kutlu-cikm18.pdf>, SIGIR’18 <https://www.ischool.utexas.edu/~ml/papers/kutlu-sigir18.pdf>, ECIR’19 <https://www.ischool.utexas.edu/~ml/papers/gupta-ecir19.pdf> (award), ICTIR’20 <https://www.ischool.utexas.edu/~ml/papers/rahman-ictir20.pdf> - Multi-objective optimization: ICTIR’21 <https://utexas.box.com/v/gupta-ictir21>, UAI’22 <https://utexas.box.com/v/gupta-uai2022> - Supporting content moderators: HCOMP’20 <https://www.ischool.utexas.edu/~ml/papers/das_hcomp20.pdf>, CHI’21 <https://www.ischool.utexas.edu/~ml/papers/steiger-chi21.pdf> About UT Austin <http://www.utexas.edu/about/overview>. UT Austin is a nationally ranked, tier-one research institution. The university offers competitive salaries and benefits, an extensive support network, and above all, an enriching and highly collaborative community. Our Information School <https://www.ischool.utexas.edu/> (iSchool) is top-ranked <https://www.ischool.utexas.edu/news/texas-ischool-remains-top-tier-us-news-grad-school-rankings>, and UT Austin has fantastic opportunities across campus in Computing Research <http://computing.utexas.edu/research>, such as our interdisciplinary Machine Learning Lab <https://ml.utexas.edu/> (including a NSF National Artificial Intelligence Research Institute <https://beta.nsf.gov/funding/opportunities/national-artificial-intelligence-research-institutes>, the IFML <https://ifml.institute/>). Our university also boasts one of the world’s largest supercomputers <https://www.tacc.utexas.edu/> to facilitate compute intensive research (e.g., with clusters of large memory GPUs). Last but not least, the selected postdoc will have the opportunity to engage with researchers across campus in Good Systems <http://goodsystems.utexas.edu/>, an eight-year, Grand Challenge at UT Austin to design responsible AI technologies. About Austin, TX. Austin is one of the USA's sunniest and most vibrant cities in which to live and work. Our large and growing high-tech hub has further earned it the moniker of being the USA's "Silicon Hills <https://en.wikipedia.org/wiki/Silicon_Hills>". See https://www.austintexas.org/things-to-do/ How to Apply. Please email Matt Lease ([email protected]) with the subject "postdoc application”. Your email should: - Provide a current curriculum vitae (URL is fine) - Describe your interest and fit for the position - Describe one or more research projects or areas you would like to pursue. A formal Research Statement document is not required but welcome if available. Interviews will be conducted remotely via zoom, and candidates will be expected to present their research as part of the interview process. About the Faculty Supervisor. Matt Lease <http://www.ischool.utexas.edu/~ml> is a faculty member in the School of Information, with a secondary appointment in Computer Science <https://www.cs.utexas.edu/people/faculty-researchers/matthew-lease>. Lease is also an Amazon Scholar <https://www.amazon.science/scholars> in AWS’s Human-in-the-loop science team. Lease received early career awards from the NSF, IMLS, and DARPA. Recent honors include JAIR’s Award Winning Papers Track (2020), Best Student Paper at the European Conference for Information Retrieval (2019), and Best Paper at the Association for the Advancement of Artificial Intelligence (AAAI) Human Computation and Crowdsourcing conference (2016). Lease is a faculty founder and leader of Good Systems <http://goodsystems.utexas.edu>, an eight-year, university-wide Grand Challenge at UT Austin to design responsible AI technologies. Equal opportunity employment. The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions. -- Matt Lease Associate Professor School of Information University of Texas at Austin Voice: (512) 471-9350 · Fax: (512) 471-3971 · Office: UTA 5.536 http://www.ischool.utexas.edu/~ml
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