Assistant Prof/Associate prof/ Prof in Data Science and Artificial Intelligence

Muscat University; Muscat; On-site; OMR 30,000 - 50,000; Full time

Job summary

Muscat University seeks an Assistant Professor/Associate Professor/Professor in Data Science and Artificial Intelligence. This role focuses on teaching at postgraduate and undergraduate levels, engaging in research, and developing curriculum aligned with industry standards.

The ideal candidate will have a PhD in a related field, proven teaching and research experience, and practical expertise in AI applications. Commitment to community engagement and curriculum innovation is vital.

Qualifications

• PhD in a relevant field from an internationally recognized university.
• Experience teaching at undergraduate and postgraduate levels.
• Demonstrated engagement in research activities.
• Experience in AI applications or data analytics preferred.

Responsibilities

• Teach Data Science and AI modules at various levels.
• Supervise student projects and theses.
• Engage in research leading to publication.
• Develop curriculum and enhance programs based on industry needs.

Skills

Teaching experience in Data Science and AI

Research engagement in Data Science

Practical computing and analytical skills

Expertise in Machine Learning and Deep Learning

Programming skills (e.g., Python/R)

Education

PhD in Data Science or related field

Tools

Machine learning frameworks

Cloud or big-data platforms

Job description

Assistant Prof/Associate Prof/Prof in Data Science and Artificial Intelligence

Position Title

Reports to Dean – Faculty of Engineering and Technology

Purpose of the Position

This is a predominantly teaching-focused position to manage and support the delivery of postgraduate, undergraduate, foundation and executive programmes.

Applicants should demonstrate excellence in teaching and research. Preference will be given to candidates with administrative experience. The successful candidate is expected to:

Teach Modules – Deliver modules at both undergraduate and postgraduate levels in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, Data Analytics, and related computing areas, while supervising postgraduate theses. The normal teaching load is 3‑4 modules per semester (2 semesters per academic year).

Supervise Projects – Oversee undergraduate and postgraduate projects and dissertations, ensuring students receive guidance on their research methodologies, implementation, experimentation, and outcomes.

Engage in Research – Actively participate in scholarly research activities that lead to publications in refereed, indexed, and ranked international journals within the fields of Data Science, Artificial Intelligence, and related interdisciplinary domains.

Collaborate for Grants – Initiate and develop research collaborations that result in successful research grant applications, enhancing the department’s funding and research capabilities.

Curriculum Development – Play a significant role in curriculum development, programme enhancement, graduate supervision, and quality assurance while supporting the introduction of innovative AI‑ and data‑driven learning content.

Lead Research Output – Produce high‑quality scholarly work that contributes to the department’s research output and enhances its academic reputation.

Community Engagement – Participate in service activities for the university as well as professional and local communities, promoting the importance of Data Science, Artificial Intelligence, and emerging digital technologies.

Key Responsibilities

• Deliver a high‑quality teaching experience in foundation, undergraduate (Data Science and AI), laboratory, postgraduate programmes and in executive programmes.
• Ensure all necessary content and material is in place for the degree programmes in time.
• Construct and plan student assignments, module delivery and assessment, ensuring coherence and relevance.
• liaise with the Faculty Dean on all student matters and timetable planning and manage module timetables, content and resource areas, liaising with academic and technical staff as appropriate.
• Initiate high‑quality learning and teaching/training activities that reflect the needs and contemporary currency of the subject and to foster a group dynamic and peer learning.
• Engage with students and demonstrators during laboratory sessions to ensure a high level of understanding is achieved by the students.
• Ensure all learning experiences comply with the expectations of all related standards of the Oman Academic Accreditation Authority (OAAA).
• Monitor the student voice through meetings, surveys and reviews and liaise with the Faculty Dean in relation to findings, initiating solutions to any student dissatisfaction or other issues.
• Formulate and coordinate the Final Year Projects and Theses to ensure a consistent and rigorous process, including liaising with industry where necessary.
• Attend Open Days, external events and interviews as required by the Faculty Dean to support recruitment activities.
• Maintain flexible working patterns which include some evening and weekend work in support of Programme/Faculty/University business.
• Actively engage with businesses/professional bodies/schools and colleges/communities/enterprises, organize student outreach and invite industry speakers to enhance the student experience and facilitate industrial placement of students, as appropriate.
• Organize, prepare and participate in University meetings and events including Boards of Examiners, Programme Reviews, Planning and Monitoring committees, Student/Staff Liaison, and faculty and university committees and policy developments.
• Work with the Faculty Dean and other University representatives to ensure student attainment, success and progression by monitoring student attendance and performance, and obtaining student feedback.

Qualifications, Experience & Competencies

• Educational qualifications: A PhD in Data Science, Artificial Intelligence, Computer Science, Information Systems, or a related area from an internationally recognized university.
• Specialization areas: Expertise in one or more of the following areas: Machine Learning, Deep Learning, Generative AI, Natural Language Processing, Computer Vision, Data Mining, Big Data Analytics, Business Intelligence, Statistical Learning, Reinforcement Learning, AI Ethics, or Intelligent Systems.
• Teaching experience: Demonstrated experience teaching Data Science and AI‑related courses at both undergraduate and postgraduate levels and supervising research projects.
• Research engagement: Active involvement in research within their areas of specialization, showing intellectual engagement with current trends, methods, and challenges in Data Science and Artificial Intelligence.
• Industry experience: Preference will be given to candidates with relevant industry experience in AI applications, data analytics, digital transformation, or intelligent systems that complement their academic qualifications.
• Practical skills: Candidates should possess strong practical computing and analytical skills relevant to their areas of expertise, including programming (e.g., Python/R), data visualization, machine learning frameworks, and cloud or big‑data platforms where applicable.
• Professional development: Relevant professional certifications or evidence of continuing professional development in AI, data science, cloud analytics, or related technologies will be an advantage.
• Community participation: Evidence of active participation in university, professional, and local community initiatives related to Data Science, Artificial Intelligence, and innovation.
• Priority in recruitment shall be given to Omani Candidates.

While we value the interest shown by every applicant, we are able to respond only to short‑listed candidates.