Computational Science and Engineering, Ph.D.

The Computational Science and Engineering Ph.D. program at Harrisburg University is a comprehensive, interdisciplinary initiative designed to foster innovative research at the intersection of computational science and engineering. This program equips the student with the intellectual skills necessary to navigate and contribute to the rapidly evolving landscapes of both disciplines. By integrating computational methods with engineering applications, the curriculum prepares the student to address complex problems across various sectors, making them competitive for external research funding and leading-edge research opportunities. 

Mission Statement

The Computational Science and Engineering Ph.D. program is an academic, research-intensive graduate program committed to multidisciplinary education and pioneering research. The program is tailored for students who require intensive use of advanced computation, computational methods, and innovative engineering solutions in their doctoral research. It is particularly suited for those exploring high-impact applications in both the computational and engineering domains. A deep understanding of both computational theories and engineering practices is crucial for success in this program.

Program Goals

The Ph.D. Computational Science and Engineering Program will produce graduates who:

• Analyze complex, interdisciplinary problems and formulate computational strategies to solve them effectively;
• Design and conduct original research that advances scientific understanding and fosters innovation;
• Develop and implement computational and engineering solutions using contemporary tools and methodologies;
• Create novel solutions and evaluate their societal and market potential to generate meaningful impact and innovation;
• Demonstrate ethical reasoning and apply professional standards in the responsible use of data, technologies, and scientific practices;
• Assess the societal, environmental, and global implications of computational and engineering work and integrate that awareness into decision-making; and,
• Collaborate across disciplines and sectors to apply research in real-world and professional contexts.

*Work experience is a requirement for successful applied learning during the full course of your degree program. If you are an F1 student, eligible CPT authorizations are required. If you are unable to work, you must submit a Waiver of Required Work Experience to your program lead.