Lecturer (Artificial Intelligence, Machine Vision & Computer Science)

Lecturer (Artificial Intelligence, Machine Vision & Computer Science)

Inspire the next generation of AI talent. Teach. Innovate. Transform.

We are looking for passionate and driven Lecturers who specialise in Artificial Intelligence, Machine Vision, Big Data Analytics, Deep Learning, or Computer Science. If you enjoy teaching, sharing real‑world experience, and shaping future tech professionals, this role is for you.

You will deliver engaging lessons, support student learning, and contribute to the growth of a dynamic and fast-evolving academic discipline.

What You Will Teach

Candidates should be able to teach 2 to 3 subjects from the following areas:

• Machine Learning
• Knowledge Graphs
• Data Mining
• Robotics
• Knowledge Representation & Reasoning
• Autonomous & Autonomic Intelligent Systems
• Data Analytics & Artificial Intelligence
• Effective Research & Professional Practice
• Artificial Intelligence Planning

Your Role

As a Lecturer, you will:

• Plan and deliver engaging lessons that promote active learning.
• Use modern teaching tools and technologies to enhance learning.
• Provide clear learning objectives, materials, and guidance.

• Monitor and evaluate student progress.
• Give constructive feedback and academic support.
• Maintain accurate student performance records and reports.

• Prepare classrooms and resources for lessons.
• Adapt teaching methods to meet diverse learning needs.
• Maintain a safe, disciplined, and motivating classroom environment.

• Participate in departmental meetings and school activities.
• Support extracurricular programmes, student engagement, and academic events.
• Stay updated with the latest trends, research, and teaching methods in your field.

• A PhD (or equivalent) in Artificial Intelligence, Computer Science, Machine Vision, or related area.
• Teaching qualifications (ACTA / ACLP / SDALT / GCTLHE / PGCHE / DACE) are advantageous.
• 3–5 years of relevant work or teaching experience in the field.
• Passion for teaching and mentoring students.
• Ability to integrate real‑world industry knowledge into lessons.
• Strong communication, presentation, problem‑solving, and class‑management skills.
• Student‑focused, adaptable, and committed to continuous improvement.