FACULTY SEARCH: Rice University’s Data Science Initiative

The International Society for Bayesian Analysis

Houston (TX)

Sur place

USD 80 000 - 120 000

Plein temps

14 jours+

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Résumé du poste

Rice University seeks to hire multiple tenure-track faculty for its Data Science Initiative. The roles focus on theoretical and applied research in data science, with opportunities across various departments and a commitment to diversity and excellence.

Qualifications

  • Candidates must possess a PhD or be near completion by November 1.
  • Research statement should align with data science applications in health, urban analytics, or high-velocity data.

Responsabilités

  • Contribute to theory, algorithms, and systems in data science.
  • Research applications in health and urban analytics.

Connaissances

Theory of data science
Algorithm design
Data-intensive science

Formation

PhD in relevant field

Description du poste

FACULTY SEARCH: Rice University’s Data Science Initiative

Sep 6, 2017

Rice University, as part of its $150 million investment in research excellence, intends to hire multiple tenure-track faculty members whose research focus is in data science. These new hires will join the four faculty members hired in the 2016-2017 academic year, along with the community of scholars at Rice who focus on data-driven research. We seek to hire two distinct kinds of specialists: (1) data scientists who can make fundamental contributions to the theory, algorithms, and systems aspects of data science, and (2) scholars who work on emerging applications of data science to problems in health and medicine, urban analytics, and high-volume or high-velocity data-intensive science. The candidate’s cover letter or research statement should make clear how their research relates to one of these three problem areas.

The Data Science initiative seeks candidates at all ranks, for employment as early as July 1, 2018. All new hires will have an appointment in one or more relevant department. Assistant Professors will have a single primary department that will be responsible for their mentoring and promotion. At higher ranks, appointments across multiple departments are desirable. Individual departments at Rice also have active faculty searches this year. Those searches are distinct from the Data Science search and may include research areas beyond those included in the Data Science search. Interested candidates should consider applying to both the Data Science search and any appropriate departmental search.

Applicants to the Data Science search should submit the following: (1) cover letter; (2) curriculum vitae; (3) research statement which describes how the candidate’s work fits with Rice’s data science initiative and in one or more of the three problem areas (not to exceed three pages including figures); (4) teaching statement; and (5) the names, professional affiliations, and email addresses of three references. For full details and to apply, please visit: http://jobs.rice.edu/postings/11380. These positions require a PhD, or PhD requirements fulfilled by November 1 of the year employment commences. Applications will be evaluated beginning on September 15, 2017 and will continue to be accepted until all positions are filled. Recommendation of candidates or questions regarding this opportunity can be directed to the committee at datascience@rice.edu.

Rice University, located in Houston, Texas, is a private, coeducational, nonsectarian university that aspires to path-breaking research, unsurpassed teaching, and contributions to the betterment of our world. Rice fulfills this mission by cultivating a diverse community of learning and discovery that produces leaders across the spectrum of human endeavor. From its beginning in 1912, Rice has been dedicated to excellence in all regards.

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.

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