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Deep Learning in Microbiome Research

As part of the cluster hire, the Department of Statistics invites applications for a tenured or tenure-track faculty position at the rank of Assistant or Associate Professor in the broad area of artificial intelligence and microbiome research. The position starts on August 1, 2023 and is an academic year appointment (9 months) with an opportunity to supplement the salary during the summer.

Candidates with a demonstrated ability to establish a research program utilizing artificial intelligence and leveraging deep learning, machine learning, and statistical computing methods are of interest. In particular, we seek a candidate who can support the Environmental AI cluster with transformative research that can contribute to answering a variety of environmental and health-related questions, which includes analyzing microbial community and spatio-temporal data, knowledge extraction, disease predictions in human health, and environmental quality, among others. Please see the requirements for Assistant and Associate Professors in the Unit Criteria for Promotion and Tenure for the Department of Statistics (pgs 8-12).

Applicants must have a Ph.D. degree in Statistics or a related discipline. The successful applicant at the Associate Professor level will be expected to have a strong collaborative research program with external funding and be engaged in the supervision of dissertation research. The successful applicant at the Assistant Professor level will be expected to develop a research program that will be competitive for external funding. Candidates are also expected to contribute to teaching courses in statistics and environmental AI at the undergraduate and graduate levels, be engaged in the activities of the department, and contribute to service to the department, university, and the profession.

Review of applications begins October 31, 2022 and continues until filled. All applications received by October 31, 2022 will receive full consideration. Applications should include: 1) cover letter, 2) curriculum vitae, 3) research statement highlighting interest in and contributions to Environmental AI research, 4) teaching statement, and 5) statement on commitment to diversity, equity and inclusion. Applicants should also provide names and contact information for at least 3 references using the online system.

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