Postdoctoral Fellowship in Data Driven Optimization, Duke University

Project Summary

We are seeking an exceptional candidate to work with Robert Calderbank and Vahid Tarokh on Data-Driven Optimization with non-conves time-varying objectives at the Information Initiative at Duke.

Themes and Categories
Contact
Kathy Peterson
kathy.peterson@duke.edu

Applicants are expected to hold a Ph.D. degree in Math, Stat, EE, CS, 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 is expected to have a background and familiarity with some of these topics: Model Matching, Expert Systems, Information Theory, and Online Optimization Methods. Familiarity with at least one programming language is required.

This effort has been funded by a generous grant from DARPA. The original appointment period is for one year (beginning April 1, 2018).

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.  Please submit your application to Ms. Kathy Peterson by email kathy.peterson@duke.edu.

Applications received by March 31, 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.

Related Projects

We are seeking an exceptional researcher to work with Vahid Tarokh at the Information Initiative at Duke on foundations of Non-Commutative Information Theory, and the Design of Algorithms for the Processing of Multimodal Data based on these theoretical findings.

We are seeking up to two exceptional researchers to work on calculation of Fundamental Limits of Learning for High Dimensional, Purely High dimensional data, Sparse Data, and the Design of Limit Achieving Algorithms to work with Vahid Tarokh at the Information Initiative at Duke.

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.