Laboratory for Autonomy, Control, Information, and Systems (LACIS) of the University of South Florida (USF) is looking for exceptional Ph.D. students with creative skills and a solid background in dynamical systems and control theory. Expected start date is the beginning of Summer 2023 and/or the beginning of Fall 2023. These students are expected to perform high-quality scholarly work related to our research focus areas (details below in Section 1). Our intention is to give a strong guidance to maximize the changes of our students for building a rewarding career (see below Section 2 for a summary on what happened to our former students after they graduated from LACIS). If you are interested in joining the LACIS to do transformative discoveries to make the impossible happen, please see Section 3 below on how to apply.
1. Research Focus Areas at LACIS
The interdisciplinary research performed by the LACIS is focused on the discovery of novel control, information, and decision systems that reveal next generation highly capable autonomous vehicles and robotic swarms (multiagent networks). These systems are envisioned to elevate our society and perform safety-critical applications. The LACIS Director, Dr. Tansel Yucelen, places a strong emphasis on both theoretic research and experimentation for addressing fundamental and open real-world technological problems. Our research is particularly focused on i) adaptive and robust control of safety-critical systems; ii) distributed estimation and control of networked multiagent systems; iii) resilient and secure robotics, autonomous vehicles, human-in-the-loop systems, and cyber-physical systems; and iv) biologically-inspired complex, large-scale, and modular systems. In these research focus areas sponsored by NSF, AFOSR, AFRL, NASA, ARO, DARPA, and ORAU, people at the LACIS authored more than 300 archival journal and conference publications, gave numerous talks and seminars, have conducted externally supported research, and have performed several technology transitions. Our aim is to be recognized as one of the top research laboratories around the globe on systems and control by significantly advancing the knowledge through innovative discoveries and training science-based engineers and professionals to shape the future of our society!
2. About Our Former Students
We have an exceptional track record with regard to our all former graduated students from LACIS. Specifically, several of them are now at academia (as Postdoctoral Researchers and Assistant Professors), several of them are now at top research laboratories (including Air Force Research Laboratory, Army Research Laboratory, and Sandia National Laboratories), and several of them are now at top companies (including Lockheed Martin, Ford Research Laboratory, and Combine).
3. How to Apply
Please send an email to Dr. Tansel Yucelen (yucelen@usf.edu), LACIS Director, and include the following material as a single PDF attachment to your email in the below order:
a) Your curriculum vitae
b) Explanation of your theoretical and/or experimental background related to dynamical systems and control theory.
c) List of your undergraduate and graduate courses taken related to dynamical systems and control theory (include your grades).
d) If any, include a published paper of yours (please do not share under review or to-be-submitted manuscripts).
e) Contact information for two references (include their name, position, and email address).
f) Your citizenship (several of our ongoing and expected projects require U.S. Citizenship and others does not have such a requirement, and therefore, it is important to know your citizenship).
Note: We will only consider candidates that have background in dynamical systems and control theory. Owing to the advanced nature of our ongoing and expected projects, preference with be given to candidates who already have taken undergraduate and graduate courses related to dynamical systems and control theory such as linear control systems, nonlinear control systems, optimal control systems, robust control systems, and/or control theory applications to autonomous vehicles and robotic swarms.
