Assistant Prof/Associate Prof/ Prof in Data Science

Muscat University; Muscat; On-site; OMR 40,000 - 60,000; Full time

Job summary

Muscat University is seeking a qualified professional to teach Data Science and AI modules at both undergraduate and postgraduate levels. The successful candidate will supervise projects and engage actively in research activities, contributing to publications in reputable journals.

The role requires a PhD in a relevant field and demonstrated teaching and research experience, as well as involvement in community initiatives related to Data Science and AI.

Additional responsibilities include curriculum development and community engagement, ensuring a high-quality educational experience for students.

Qualifications

• PhD in Data Science or a related area is required.
• Demonstrated teaching experience in Data Science and AI courses.
• Active research involvement in Data Science and AI.

Responsibilities

• Teach modules in Data Science and AI at undergraduate and postgraduate levels.
• Supervise student projects and theses.
• Engage in research and publish in recognized journals.

Skills

Machine Learning

Deep Learning

Data Science

Artificial Intelligence

Data Analytics

Education

PhD in Data Science, Artificial Intelligence, Computer Science, Information Systems

Tools

Python

R

Machine Learning frameworks

Cloud platforms

Job description

Teach 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 and 2 semesters per academic year.

Supervise Projects: Oversee undergraduate and postgraduate projects and dissertations, ensuring students receive guidance on 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., organise student outreach and invite industry speakers to enhance the student experience and facilitate industrial placement of students where appropriate.
• Organise, 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.
• Any other duties as deemed necessary by the Line Manager.

Application Requirements

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

Qualifications

• PhD in Data Science, Artificial Intelligence, Computer Science, Information Systems, or a related area from an internationally recognized university.
• 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.
• Demonstrated experience teaching Data Science and AI‑related courses at both undergraduate and postgraduate levels and supervising research projects.
• Active involvement in research within their areas of specialization, showing intellectual engagement with current trends, methods, and challenges in Data Science and Artificial Intelligence.
• Preference given to candidates with relevant industry experience in AI applications, data analytics, digital transformation, or intelligent systems that complements their academic qualifications.
• 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.
• Relevant professional certifications or evidence of continuing professional development in AI, data science, cloud analytics, or related technologies will be an advantage.
• Evidence of active participation in university, professional, and local community initiatives related to Data Science, Artificial Intelligence, and innovation.