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. Funding includes tuition, a 12-month stipend of up to $2000/mo, travel and expenses. A Fall 2019 start is anticipated, although applications will accepted until October 1, 2019 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) by USNews and 51-75th globally (6) by ARWU in 2015.
The candidate should have an aptitude for mathematics who is interested in solving fundamental and high-impact, difficult problems in the fields of optimization, control and machine intelligence.
The research project proposed here is advanced optimization techniques for control over communication networks. Potential examples include control of remote and autonomous systems, including fleets of self-driving cars, remote spacecraft, and fleets of UAVs. Our lab has made dramatic progress in this area in recent years and our algorithms are currently the most accurate, reliable, and scalable of any lab in the world.
Eligibility: Students must have a minimum of first class honors or equivalent from a top 100 university as per AWRU, USNWR or other major ranking system (2.1 OK for Oxford/Cambridge). For non-UK students, an undergraduate GPA of 3.6 (US), 90 (China), 18(Iran), 8(India), 9.0 (Mexico) is required. In addition, an interview will be conducted to screen for academic aptitude.
Particularly relevant skills can include a background in Algorithms, Mathematical analysis, Optimization, and all areas of Control. Candidates should have an undergraduate degree in Engineering, Mathematics, or a related discipline.