The Departments of Statistics and of Computer Science at Rice University are seeking candidates for two postdoctoral research associate positions, as part of a recently awarded Research Training Groups in Mathematical Sciences (RTG) grant (http://as102.http.sasm3.net/awardsearch/showAward?AWD_ID=1547433). The successful candidates will work with faculty members and graduate students in both Statistics and Computer Science to develop innovative methodologies for data science. The positions will involve working closely with faculty members to develop and teach a new course on data science that will be offered to graduate and advanced undergraduate students who participate in the Research Training Group. Highly motivated and qualified candidates with research experience in areas such as statistical inference and machine learning are encouraged to apply. A Ph.D. in Statistics, Computer Science, or related fields is required. This opportunity is restricted to U.S. citizens or Permanent Residents only.
Review of applications will begin immediately. To apply, please refer to https://jobs.rice.edu/postings/8328. Please submit a cover letter, a curriculum vita, a research statement, two representative publications, and contact information for three references. For more information, please contact Phyllis Huitron at Phyllis@rice.edu. The positions will remain open until filled.
Rice University has recently announced a $150 million investment in research excellence, with data science identified as one of the core areas in this investment. As part of this initiative, Rice University is also broadly hiring faculty members (http://datascience.rice.edu) and post-doctoral research associates (http://www.riceacademy.rice.edu/).
Rice University, located in Houston, Texas, is a private, coeducational, nonsectarian university. Rice University is an Equal Opportunity Employer with commitment to diversity at all levels, and considers for employment qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national or ethnic origin, genetic information, disability or protected veteran status.