Ph.D. Opportunity in High-Performance & Quantum Computing | UNC Charlotte

University of North Carolina

0

Vacancy

2

Description

The University of North Carolina at Charlotte (UNC Charlotte) is actively seeking a highly motivated Ph.D. student to join a dynamic research group starting as early as Spring 2027. This research opportunity focuses on the design of advanced algorithms for large-scale combinatorial problems and their deployment on modern high-performance computing (HPC) systems. The chosen candidate will have the chance to explore cutting-edge applications across machine learning, computational science, and engineering. For this specific recruitment cycle, the research group is particularly interested in scholars eager to delve into quantum computing applications. Students passionate about computing innovations and advanced algorithmic structures are highly encouraged to apply.


Responsibilities

Research Focus

The selected Ph.D. student will engage in rigorous academic research and practical problem-solving. Key responsibilities include:

  • Designing and evaluating advanced algorithms tailored for large-scale combinatorial problems.
  • Implementing computational solutions on modern high-performance computing (HPC) architectures.
  • Exploring and developing innovative applications within the emerging field of quantum computing.
  • Applying algorithmic frameworks to address complex challenges in machine learning and computational engineering.


Qualification

Candidate Profile

To be considered for this research group, applicants should demonstrate strong academic potential and a genuine curiosity for computational sciences. The ideal candidate will meet the following criteria:

  • A strong academic background in Computer Science, Engineering, Mathematics, or a closely related quantitative field.
  • A demonstrated excitement for studying advanced algorithms and complex problem-solving.
  • A keen interest in high-performance computing (HPC) systems and their modern applications.
  • Specifically seeking candidates with a strong desire to explore quantum computing (highly prioritized for this cycle).
  • Prior academic exposure or research experience in machine learning or combinatorial optimization is highly valued.


Application Procedure

Candidates ready to advance their research careers at UNC Charlotte should follow these application steps carefully:

  • Prepare Your Documents: Update your Curriculum Vitae (CV) to highlight your academic background, relevant skills, and any previous research experience. Write a brief but clear explanation of your specific research interests and why you are motivated to join this particular research group.
  • Submit via Email: Send your application materials directly to the principal investigator at sferdou1@charlotte.edu.
  • Required Subject Line: You must format your email subject line exactly as follows: “PhD Interest at UNC Charlotte – [Your Name]”.


Key Dates & Deadlines

Program Start Date: As early as Spring 2027.

Deadline: Applications are reviewed on a rolling basis. Interested students are encouraged to reach out as soon as possible.

Circular Summary
Ph.D. Opportunity in High-Performance & Quantum Computing | UNC Charlotte

Published on: 24th September 2026

Employment Status:

Country: United States

Views: 83

Application Deadline: 31st December 2026

Updated on: 9th October 2026

Similar Circulars

Fully Funded Ph.D. Positions in Robotics at the University of West Florida (Spring 2027)

University of West Florida

The University of West Florida (UWF) is actively seeking one to two motivated Ph.D. students to j...

Ph.D. Positions in Civil Engineering at Louisiana Tech University – Winter 2026-27

Louisiana Tech University

Louisiana Tech University is actively seeking highly motivated graduate students to fill two Ph.D...

Ph.D. Position in Civil and Environmental Engineering - University of New Mexico

University of New Mexico

The Gerald May Department of Civil, Construction and Environmental Enginee...

We use cookies!🍪

We value your privacy and use cookies to enhance your browsing experience, personalize content, and analyze site traffic. You can review our Cookie Policy to know more about how we use cookies and manage your preferences. By clicking 'Accept', you agree to our use of cookies. Read more