Open date: August 5th, 2020
Next review date: Friday, Oct 2, 2020 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.
Final date: Friday, Oct 23, 2020 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
Join us as a postdoctoral research fellow in the Language and Learning Analytics Laboratory (LALA-Lab) at the University of California, Irvine’s School of Education. This postdoctoral fellowship includes a very competitive salary of ~$80,000 a year plus benefits. In addition, the fellow will be given a budget for research assistants, travel, and discretionary funds. This position is for 1 year, renewable for a second year (and potentially a third). The anticipated start date will be September 2020, with some flexibility for the availability of the applicant. The candidate will work under the supervision of Dr. Nia Dowell and will play a collaborative and co-leadership role in a vibrant research team.
About the position
The successful candidate will conduct research in educational data science, learning analytics, speech and natural language processing (NLP) to solve challenging and impactful, real-world problems. They will participate in the development and application of advanced NLP and machine learning techniques to multi-party text and speech data collected in authentic contexts (e.g., large and small group collaborative problem solving). They will also participate in the design and development of real-time automated feedback systems for collaborative interactions.
This is a full-time postdoctoral research position funded by the Bill and Melinda Gates Foundation project “Learning engineering post-doctoral fellowship”, which is being led by PI Justin Reich (MIT) with co-PIs Ken Koedinger (CMU) and Nia Dowell (UCI). The goal of this grant is to provide support for scholars who are Black, Latinx, first generation Americans and/or impacted by poverty to pursue research into learning engineering and to engage in projects that focus on promoting inclusivity and equity for under-represented populations.
The position offers a unique postdoctoral training experience and unsurpassed publishing opportunities within multi-department and multi-institution grant-funded projects. The successful candidate will be encouraged to develop new technical skills, strengthen their portfolio of peer-reviewed publications, gain interdisciplinary experience, develop leadership, and gain expertise in co-authoring grant proposals.
About the lab
The Language and Learning Analytics Laboratory (LALA-Lab) brings together an interdisciplinary group of students and faculty who explore the intersections of technology with teaching, learning, and education, with a particular focus on learning analytics, educational data mining, and collaborative engagement. Led by Dr. Nia Dowell, Assistant Professor in Education at UC-Irvine, the LALA-Lab includes researchers with backgrounds in cognitive science, education, information, psychology, and statistics. The LALA-Lab takes a multi-disciplinary approach that builds on theories and methods in the learning sciences, cognitive psychology, human-computer interaction, and computational social sciences. Dr. Dowell and her team conduct basic research on socio-cognitive and affective processes across a range of contexts, focusing in particular on interactions within educational technology and develop computational models of these processes and their relationship to learner outcomes. Their research uses a range of advanced techniques such as computational linguistics and machine learning. Current projects focus on:
i. understanding differences in students’ socio-cognitive engagement patterns across gender and racial lines
ii. identifying interpersonal dynamics that characterize varying levels of creativity/innovation and sense of belonging during collaborative interactions, and
iii. developing AI-based interventions to promote inclusivity in digitally-mediated team problem-solving environments.
Applicants should have a doctorate in information sciences, cognitive science, human-computer interaction, computer science, learning sciences, learning analytics, psychology, design, or a related field. They should have completed strong, compelling PhD research in one (or more) of these areas. Questions about the position may be addressed to Nia Dowell, Asst. Professor at email@example.com.
-Ph.D. in Information Sciences, Psychology, Computer Science, Cognitive Science, -Artificial Intelligence, Learning Sciences or a related field at the time of hire
-Candidates must have had experience as or identify as First Generation American, Black, Latinx, and/or impacted by poverty and be committed to doing research that positively impacts students with those experiences/identities
-A strong research record, documented by recent publications in top-tier conferences and journals
-Good communication skills and fluency in English
-Strong computational and analytical skills, especially the ability to develop software and/or perform sophisticated data analysis
-Highly motivated and creative, enjoys working in a collaborative research environment
Research experience in one or more of the following areas: software development, advanced machine learning and data mining, learning analytics, natural language understanding, discourse modeling
To Apply: Applications should be submitted online at https://recruit.ap.uci.edu/apply/JPF06318
Please include a cover letter explaining your relevant background and interest in this project, CV, 1-2 sample publications, and names of three references (please do not solicit letters). Review of materials will begin immediately and will continue until the position is filled.
The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.
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