We enthusiastically invite multiple interdisciplinary researchers to join our newly established Department of Data Science as tenure-track faculty colleagues. We invite applications from researchers working in Data Science, broadly defined, including those working in other domains who contribute to data analysis methodology for that domain (e.g., methods and/or applications of artificial intelligence, machine learning, statistical inference, computational/applied mathematics, data visualization, etc) as well as those whose research focuses directly on the methodology itself (e.g., computer science or statistics). We are building the Data Science department to center justice, diversity, equity, and inclusion (JDEI), in our department’s research, teaching, and organization. Strong faculty candidates will therefore have demonstrated impactful contributions to JDEI. We encourage applications from candidates with a history of collaboration with domain experts.

Strong candidates will have excellent research scholarship; as befits an inclusive, interdisciplinary department, we are open to various metrics of research success beyond grants, citations, and publications (including policy impact, community engagement in research, collaborative projects, et cetera). Strong candidates will have demonstrated excellence in and commitment to teaching, translation of knowledge, or advising/mentoring of students (including out-of-classroom education). We are excited to grow a mutually supportive culture of impactful teaching and research in our new department. We seek candidates who are enthusiastic to help develop our department culture of inclusive excellence, and have demonstrated this through past service. We welcome candidates who understand the barriers facing members of groups who have been historically excluded from data science and higher education (as evidenced by life experiences and educational background), and who have experience in JDEI with respect to teaching, mentoring, research, outreach, life experiences, or service towards building an equitable and diverse scholarly environment.

More information about the Data Science department can be found at https://scds.uoregon.edu/ds. Particular strengths of collaborative research at UO include environmental science, ecology, evolution, linguistics, cell and developmental biology, sport and wellness, earth science, and spatial information sciences.