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Advanced Study in Machine Learning and Automatic Control. Methods and Application to Immunotherapy.

  • Full or part time
  • Application Deadline
    Tuesday, September 01, 2020
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

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. 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.

I am looking for a student or students interested in understanding and solving the problems which will define the future of machine learning and automatic control algorithms. The student should have a strong interest in Mathematics or Computation.

Machine learning and automatic control have received much attention in the media in recent years. Despite what you may have heard however, these technologies are still in their infancy. The goal of our research is to develop these methods to the point where they can impact society in the same way the internet or GPS did in the 90’s and 2000’s.

Once the student has developed the necessary skills and background, we will focus on applying our techniques to understanding how the immune system responds to antigen excitation. In collaboration with immunologists at the Mayo clinic and ASU, we will use live-animal mouse-model experiments to learn the immune response to cancer and use real-time feedback to create the next generation of immunotherapy treatments.

At the discretion of the student and PI, we may also consider integration of renewable energy resources into the power grid or guidance and navigation of spacecraft.

Our lab has a history of producing distinctive, high-impact scholarship and exceptionally talented PhD students - please browse the list of papers at control.asu.edu. A typical 4-year PhD program in the CSCL leads to multiple publications in the top Journals of Machine Learning (JMLR) and Automatic Control (TAC, Automatica) and is preparation for future employment in academia or a research institute.

ASU, based in Tempe, AZ, is the 8th largest research university in terms of enrollment (1) in the United States and 8th most active non-medical research institution in terms of research expenditures. 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.

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 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 . Additionally, students must apply separately to the university online at http://graduate.asu.edu/admissions.

Funding Notes

Funded by NSF

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