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New Mathematical Methods for Automatic Control of Human Immune Response

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  • Full or part time
    Prof Matthew Peet
  • Application Deadline
    Applications accepted all year round

About This PhD Project

Project Description

A fully funded PhD position is available in the Cybernetic Systems and Controls Lab (CSCL) in the Department of Mechanical and Aerospace Engineering at Arizona State University, starting August, 2016. Funding includes tuition, a 12-month stipend of $2000/mo, travel and expenses. Applications are accepted until June 1, 2016 or until the position is filled.

ASU, based in Tempe, AZ, is the largest research university (1) in the United States. ASU was ranked 2nd nationally (2) in the 2015 US News and World Report list of “up and coming” universities for making significant investments in academics and research. The graduate Aerospace Engineering Program at ASU was ranked 23rd (3) in US News and World Report for 2015. The Electrical Engineering Program is ranked 9th (4) in research by HERD in 2014. Overall, the graduate Engineering Program was ranked 42th nationally (5) and 51-75th globally (6) by ARWU in 2015.

The ideal candidate is an engineering student with a solid background in mathematics and who is interested in fundamentally changing the world by solving high-impact, mathematically difficult problems in the fields of dynamics, control and optimization.

The research topic is centered on the theoretical development of radically new optimization-based algorithms which will allow machines to manipulate complex nonlinear and spatially distributed systems such as the human immune system, thereby fundamentally changing how we fight disease.

Eligibility: Students must have a 2.1, first class honors or equivalent from a top 100 university as per AWRU, USNWR or other major ranking system. For non-UK students, an undergraduate GPA of 3.6 (US), 90 (China), 17(India/Iran) is required. Other countries will be considered on a case-by-case basis.

Particularly relevant skills can include a background in Physics, Algorithms, Parallel computing, Mathematical analysis, Optimization, and all areas of Control. Candidates should have an undergraduate degree in Engineering, Mathematics, or a related discipline.

If eligible, apply for the position by sending a cv, undergraduate and graduate transcripts (if relevant) directly to [email protected] Additionally, students must apply separately to the university online at


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