Texas Christian University
Fort Worth, Texas
Department of Mathematics
Applications are invited for a tenure-track assistant professor position in the research area of statistics or data science, beginning in August 2018. Qualifications include a Ph.D. in Statistics, Biostatistics, Data Science, or Mathematics with a specialization in statistics or data science by August 2018; excellent research potential; a record of outstanding teaching; and enthusiasm for mentoring Ph.D., Master’s, and undergraduate students. In particular, the Department has a thriving undergraduate actuarial concentration and, in conjunction with the Department of Computer Science, plans to introduce an undergraduate degree in data science. Candidates for this position are expected to assume a leadership role in these programs.
The candidate should apply through MathJobs (http://www.mathjobs.org/), submitting (a) an AMS cover sheet; (b) a complete vita, including a list of publications; (c) a research plan; (d) a teaching statement; (e) copies of undergraduate and graduate transcripts; and (f) three or more confidential letters of recommendation, at least one of which addresses the candidate’s teaching in detail. Candidates must also fill out a brief personal information form and upload their vita through the TCU HR system at https://tcu.igreentree.com/CSS_Faculty. Click on “Find Openings” and then select “Science and Engineering Positions.”
Formal review of candidates will begin on November 13 and continue until the position is filled. Inquiries should be directed to Greg Friedman, Search Committee Chair, at email@example.com.
Texas Christian University, founded in 1873, is a secular institution with just over 10,000 students and a reputation for excellence in teaching and noted institutional support for mathematical research. The university is located in the Dallas-Fort Worth metroplex, a vibrant metropolitan area with a population of nearly seven million people.
As an AA/EEO employer, TCU recruits, hires, and promotes qualified persons in all job classifications without regard to age, race, color, religion, sex, sexual orientation, gender, gender identity, gender expression, national origin, ethnic origin, disability, genetic information, covered veteran status, or any other basis protected by law.
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