Full-Time Lecturer - AI and Data Analytics Specialist

About the role

The University is seeking a highly motivated and qualified Lecturer with expertise in AI and Data Analytics for its ICT Department. The successful candidate will contribute to teaching, research and academic development, helping the university prepare graduates with strong technology, research, critical thinking and English skills. The role covers course delivery, student project supervision, scholarly research and collaboration with industry partners.

Key responsibilities

• Design, develop and deliver courses in AI, Machine Learning, Data Analytics, Software Development and related areas, including syllabi, lesson plans and assessments.
• Review content for other lecturers' courses and take part in curriculum development and updating.
• Supervise student research projects, internships and capstone projects, and guide students one-on-one.
• Conduct research in AI, data analytics or software engineering, publish in peer-reviewed journals, present at conferences and seek research funding.
• Support the ICT Department's operations, including organizing academic visits to industry, hackathons and competitions, and coordinating field studies.
• Manage and animate teams of lecturers, participate in departmental and university meetings, and help write program reports for the ACC and the Higher Education Department.
• Develop new courses, create pedagogical tools, and support marketing content for the ICT department.

Required profile

• At least 3 years of teaching or professional experience in AI, Data Analytics or Software Development.
• Proven experience with programming languages such as Python, Java, C++, C# or R.
• Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering or a closely related field; a PhD is an advantage.
• Evidence of scholarly publications, conference presentations or industry reports is an advantage.

Required skills

• Advanced Python, Java and C++.
• Knowledge of AI and machine learning frameworks such as TensorFlow, PyTorch and Scikit-learn.
• Data analytics tools and visualization platforms such as Power BI, Tableau and SQL.
• Software engineering practices, agile methodologies and version control (Git).
• Front-end web development (HTML5, CSS3, JavaScript, Bootstrap or a JS framework); familiarity with AWS, Azure or Google Cloud is a plus.