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

1. Purpose of the Position

This is a predominantly teaching-focused position to manage and support 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, etc., 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.
• Applicants should provide a current CV and a cover letter justifying their suitability for the position. In doing so, applicants should use their qualifications, experience in teaching and research in an HE environment, teaching areas of interest and ability, and motivation for applying to Muscat University.

Any other duties as deemed necessary by the Line Manager.

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

* The job description may be altered at any time in the future in line with the level of the post to meet changing institutional requirements, but only in full consultation with the post-holder.

Applicants are required to submit a current CV and a cover letter outlining their suitability for the position. The cover letter should clearly highlight their academic qualifications, teaching and research experience in a higher education environment, areas of teaching interest and expertise, and their motivation for applying to Muscat University.

Qualifications, Experience & Competencies:

The Department invites applications for full-time and visiting faculty positions from suitable candidates. The position within the Data Science and Artificial Intelligence programme requires:

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 complements 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.