Multiple Ph.D. positions in Computer Science with full financial support are now available starting in Spring or Fall 2023 in Dr. Christian Kümmerle’s research group in the College of Computing and Informatics at University of North Carolina at Charlotte (UNC Charlotte) in Charlotte, North Carolina, USA.
Successful applicants will receive full tuition support and monthly stipend. Possible research directions include non-smooth and non-convex optimization, scalable algorithms for data science, applications of optimization in machine learning, recommender systems and routing algorithms for payment networks. The applicants can expect a close supervision and research mentorship starting from the first year. Please refer to this website for an overview of the coursework expected in the first semesters designed to supplement your knowledge in machine learning and beyond.
Dr. Kümmerle is interested in the mathematical foundations of machine learning and the development and analysis of efficient algorithms for large scale data analysis. His research leverages continuous optimization to address computational and statistical challenges arising from data models involving graph, sparsity and low-rank structures, leading to scalable algorithms with provable guarantees, and been published at premier venues in machine learning (JMLR, ICML, NeurIPS) and mathematics.
Applicants should have a Bachelor or Master degree (or expect to receive the degree before enrollment at UNC Charlotte) in Computer Science, Applied Mathematics or related disciplines. Further admission requirements and necessary application materials can be found at the admissions page of the Computer Science Ph.D. track.
We expect enthusiasm for research and creativity from you. Applicants with strong background in multivariate calculus, linear algebra, optimization and/or hands-on programming experience in the context of machine learning (Python, scikit-learn, PyTorch, JAX) are particularly encouraged to apply.
How to Apply
To apply for the positions, please apply for the Ph.D. program in CS at UNC Charlotte and mention Dr. Kümmerle’s name in your application. Recommendation letters can be arranged to be submitted in the online application system.
Please also email your resume in PDF (including relevant research experience) to Dr. Christian Kümmerle (email@example.com) with subject line “PhD applicant”.
Applicants for Spring 2023 need to apply by October 1, 2022, early applications are encouraged. Applications for Fall 2023 are due by February 1, 2023.
All inquiries about the positions should be made to Dr. Christian Kümmerle (firstname.lastname@example.org).
UNC Charlotte & City of Charlotte
UNC Charlotte is North Carolina’s urban research institution. A large public university with a small college feel, more than 27,200 students consider UNC Charlotte’s 1,000-acre campus their home away from home. The College of Computing and Informatics is a talent-generating powerhouse and the largest producer of Computer Science graduates in NC and the sixth largest in the nation. The Computer Science Ph.D. track is with around 50 students currently the largest at UNC Charlotte and provides ample opportunities for developing advanced competencies beyond your specific research program.
Charlotte is an excellent location for you to spend your PhD years. The campus is located in the Piedmont of North Carolina, just two hours from the mountains and three hours from the Atlantic Ocean. Also known as the Queen City, Charlotte is a vibrant, entrepreneurial center and the largest city in North Carolina. Charlotte has 10 Fortune 500 companies in its metropolitan area: Bank of America, Truist Financial, Lowe’s, Nucor, Duke Energy, Sealed Air Corp, Sonic Automotive, Family Dollar, SPX Corporation, and Domtar. The city was recently named on Forbes’ list of Best Places for Business and Careers and regularly ranks highly on lists of desirable places to live and buy a home. Ranked in 2020 as America’s #1 “Tech Town”, the city has a vibrant entrepreneurial ecosystem, currently with four locally-grown unicorns (privately-held startups of at least $1B valuation).