Tenure-Track Assistant Professor in Education Statistics and Data Science
Job posting number: #7194781
Posted: November 17, 2023
Application Deadline: Open Until Filled
Job DescriptionPosition. The University of Delaware (UD) invites applications for a tenure-track assistant professor in Education Statistics and Data Science. Specifically, we are interested in scholars with primary research interests in advanced quantitative methods such as artificial intelligence, data mining, machine learning, natural language processing, network analysis, latent variable modeling, or other advanced methodological techniques. The ideal candidate would have a research portfolio that involves both developing/evaluating new statistical/computation methods and applying advanced methods to education data.
We especially value candidates who demonstrate a keen interest in collaborating with other faculty, education practitioners, and/or policymakers to design, conduct and apply research that can address critical issues facing our education systems, broadly conceived. We are particularly interested in candidates whose research addresses issues of justice, fairness and equity in education, including critical quantitative work (QuantCrit). We are deeply committed to a community of excellence, equity, and diversity and welcome applications from scholars of color, women, persons with disabilities, sexual minority groups, and other candidates who will contribute to the diversification and enrichment of ideas and perspectives. Our Educational Statistics and Research Methods (ESRM) doctoral program is a STEM-designated program and serves a high proportion of international students. We are looking for an enthusiastic individual dedicated to mentoring and closely working with students, specifically someone who is culturally responsive to meeting the needs of our growing diverse and international student body. The position will begin on August 15, 2024.
Ph.D. or Ed.D. in education, statistics, psychology, or related field by the start date, with demonstrated expertise of educational statistics and research methodology.
Demonstrated working knowledge of advanced quantitative methods in education statistics and data science.
Knowledge of and demonstrated ability to apply these advanced techniques to contemporary issues in education.
Advanced skills with computer programs such as R, Mplus, Python, SAS, and/or Stata, etc.
Evidence of a strong and established line of research and resultant research productivity in the form of peer-reviewed publications, conference presentations, and other relevant research products (e.g., R packages, book chapters).
Evidence of or interest in contributing to course offerings and program development towards the goal of applying and/or advancing quantitative and education research methodologies.
Demonstrates a respect for diversity of race, culture, and gender in viewpoints and approaches to collaboration and teaching.
Additional preferred qualifications include:
A strong record of, or potential for, obtaining external funding.
Demonstrated ability to work collaboratively with methodological and/or applied researchers across disciplines.
Prior experience and evidence of excellence in teaching and mentoring
Demonstrates the ability to incorporate the contributions of marginalized communities into their teaching, scholarly work, and/or service contributions
Has experience working with diverse student populations and communities
Responsibilities include sustaining a significant research program, supervising doctoral research as appropriate, teaching and advising in the School of Education, and performing service as assigned.
Specifically, successful candidates will:
Conduct scholarly research in developing and/or evaluating new statistical/computational methods and applying methods in collaborative work with faculty and doctoral students
Teach graduate-level courses in advanced quantitative methodologies within the School of Education
Collaborate with other ESRM faculty members on program and course design
Advise and mentor doctoral students, including as chair and/or member of doctoral (PhD) committees
Design, conduct and apply research that can address critical issues in education.