Computer Science Associate​/Assistant Professor

About CUD

Established in 2006, CUD is one of the most promising universities in the Middle East, Africa, and South Asia region, QS ranked in the top 2% of universities worldwide, #1 in Dubai, and 21st in the Arab Region according to the QS Arab Region Rankings 2025.
Our expanded City Walk campus hosts state-of-the-art amenities with a focus on entrepreneurship, innovation, and creativity. Combining all the essential elements of technology, the avant-garde campus brings a new experience to students, featuring: laboratories, research facilities, media studios, high-tech classrooms, a multipurpose theatre, gymnasium, student centre, dining and entertainment options, and more.
With one of the world’s fastest growing populations, Dubai offers a diverse, multicultural environment with outstanding lifestyle and employment opportunities.

Canadian University Dubai (CUD) is seeking exceptional faculty at the ranks of Assistant Professor and Associate Professor, in Computer Science and related disciplines to join School of Engineering, Applied Science, and Technology (SEAST).

Applicants must hold a PhD in Computer Science, or Computer Science with applied Artificial Intelligence themes. Candidates should have a strong record of teaching, research, and industry engagement in Computer Science or AI applications across domains such as computer visioning, healthcare, digital twin, education or cybersecurity.

Proficiency in Software development process, software design, software architecture is required. Hands‑on experience in one or more of web and mobile development frameworks and libraries such as React.js, View.js, Node.js, or Angular is strongly preferred.

Relevant professional certifications (e.g. IBM AI Engineering Professional Certificate, AWS Certified Solutions Architect, Microsoft Azure AI Fundamentals) are preferred.

• Assistant Professor – Minimum 2 years of undergraduate teaching experience in a top 300 QS‑ranked university, with curriculum development and graduation project supervision experience.
• Associate Professor – Minimum 5 years of undergraduate/graduate teaching experience in a top 500 QS‑ranked university, with MSc/PhD supervision experience. Familiarity with ABET accreditation is preferred.

Teaching will span five key thematic areas in Computer Science and Artificial Intelligence:

• Foundations of Computer Science, AI and Machine Learning, providing core principles and algorithms;
• Operating systems, data structure, data mining, algorithms and software paradigms, focusing on cutting‑edge techniques, large language models and emerging models;
• Computer Vision and Visual Computing, addressing image, video, and visual data processing;
• Applied AI and Emerging Technologies, integrating AI with domains such as cloud, cybersecurity, and IoT; and
• Professional Practice and Research, fostering project management, industry engagement, and scholarly inquiry.

Successful candidates will drive high‑impact research, producing 2–10 publications in reputable, peer‑reviewed journals (preferably Q1/Q2 Scopus‑indexed, commensurate with academic rank). Research should advance innovation in Computer Science, Applied Science and Artificial Intelligence while addressing global challenges through the following thematic areas:

• Scalable and real‑time AI applications – enabling responsive, high‑performance solutions for industry and society.
• AI for social good and interpretable, human‑centered AI – creating ethical, transparent systems that improve lives and foster trust.
• Integration with blockchain, edge, and cloud technologies – building secure, distributed, and sustainable digital infrastructures.
• AI policy and ethics – shaping responsible innovation and governance frameworks.

All research is expected to align with the United Nations Sustainable Development Goals (SDGs), particularly:

• SDG 3:
  Good Health and Well‑Being
• SDG 4:
  Quality Education
• SDG 9:
  Industry, Innovation, and Infrastructure
• SDG 11:
  Sustainable Cities and Communities
• SDG 13:
  Climate Action