Postdoctoral Fellowship in Change Detection for Multimodal Data, Duke University
The postdoc is at the IID center under the supervision of Prof. Vahid Tarokh.

We are seeking an exceptional researcher to work on Change Detection for Multimodal Data, and Algorithm Design with Vahid Tarokh  at the Information Initiative at Duke  https://bigdata.duke.edu/ . 

 Applicants are expected to hold a Ph.D. degree in EE, Math, Stat, Physics or a closely related field. We are seeking mathematically sophisticated and intellectually curious researchers at an early stage of their scholarly careers.

The successful candidate will have a background and familiarity with change detection literature, algorithm design and knowledge of a programing language.

This effort is funded by a generous grant from US Army Research Lab (ARL). The applicant is expected to work closely with the ARL researcher, and participate in frequent meetings and teleconferences.  Given the required security checks, US Citizenship or Permanent Residency is desired.   The original appointment period is for one year (beginning July 1, 2018), but may be extended for a second year.

Applicants are asked to submit (a) cover letter; (b) a vitae; and (c) a research statement describing current and past research (two page maximum). The applicant should request at least three letters of recommendation, but no more than five. These letters should be uploaded, by their authors, at  mathjobs.org .

Applicants are encouraged to submit all of their materials electronically at this site. Applicants who do not have internet access may mail their materials to: Appointments Committee Department of Mathematics, Box 90320, Duke University Durham, NC 27708-­0320

Applications received by June 1, 2018 will be guaranteed full consideration; early application is advisable.

Duke University seeks to build a diverse faculty: women and under-represented minorities are encouraged to apply. Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, genetic information, gender, gender identity, national origin, race, religion, sexual orientation, or veteran status.

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