Pace University

What you'll study

The PhD curriculum combines advanced coursework, formal research training and the completion of an original doctoral dissertation. Early stages of the programme typically include core and elective courses in topics such as advanced algorithms, machine learning, data mining, database systems, distributed and cloud systems, network security, software engineering and human–computer interaction. Students also take research methods courses covering experimental design, statistical analysis, and formal methods for computing, plus seminars on scholarly communication and ethics in computing research.

After completing required coursework, students take qualifying/comprehensive examinations to demonstrate readiness for independent research and then undertake an extended period of supervised research under one or more faculty advisers. The research phase culminates in writing and defending a dissertation that contributes new knowledge to a chosen subfield. Throughout the programme students are encouraged to publish in peer-reviewed conferences and journals and to participate in internal and external research collaborations.

Entry requirements

• A relevant master’s degree (for example an MSc/MA in Computer Science, Information Systems, Data Science or a closely related discipline) is normally expected; exceptional applicants with a strong bachelor’s degree and substantial research or professional experience may also be considered.
• Evidence of strong academic preparation in core computing and mathematical subjects such as programming, data structures and algorithms, probability and statistics, and linear algebra.
• A research statement or statement of purpose outlining prior research experience, research interests and proposed areas of doctoral study, and how these align with faculty expertise.
• Letters of recommendation (usually two or three) from academic or professional referees who can speak to the applicant’s research potential.
• A current CV/resume demonstrating relevant publications, projects, work experience or technical skills.
• Proof of English language proficiency for applicants whose first language is not English, where applicable.
• Additional materials that may be requested include transcripts, a sample of previous scholarly work (such as a thesis or published paper) and, in some cases, an interview with faculty.

Career prospects

Graduates of the PhD in Computer and Information Sciences pursue a range of careers in academia, industry and the public sector. Common pathways include tenure-track faculty positions, postdoctoral research roles, and research scientist or principal engineer positions in corporate R&D labs. Doctoral graduates also move into leadership roles such as data science or AI team leads, chief technology officers, and senior technical consultants, and they are well placed for research-focused roles in government agencies and non-profit organisations.

Because the programme emphasises publication and collaboration, graduates are well prepared to contribute to interdisciplinary research projects, secure research funding, and take on roles that require strong analytical, design and communication skills.

Why study at Pace University

• Pace’s School of Computer Science and Information Systems provides an environment with active faculty research across areas such as AI, cybersecurity, data analytics and human-centred computing, enabling students to find close matches with advisers and research groups.
• The University’s campuses in the New York metropolitan area offer direct access to a large technology ecosystem, including industry partners, start-ups and research labs, which supports internships, collaborations and networking opportunities.
• Students benefit from small cohort sizes and personalised mentoring from faculty, fostering close supervisory relationships and a collaborative research culture.
• Interdisciplinary collaboration is encouraged across business, health informatics and digital arts, allowing doctoral candidates to apply computing research to real-world problems and cross-domain innovation.
• Opportunities exist to present work at national and international conferences, to publish in peer-reviewed venues, and to participate in funded research projects and centres hosted by the university.