IT Lecturer - #1125136

Kaplan


Date: 10 hours ago
District: Singapore
Contract type: Full time
Work schedule: Full day
Kaplan

THE ROLE: IT Lecturer

Join our dynamic academic team at Kaplan as a Lecturer/Senior Lecturer in Artificial Intelligence, Machine Learning, Data Science, or Cybersecurity. In this role, you'll design and deliver cutting-edge lessons, guide students through hands-on learning in programming and emerging technologies, and contribute to continuous curriculum enhancement. We're looking for passionate educators who are eager to inspire the next generation of tech professionals, drive academic excellence, and shape the future of digital education.

Key Roles and Responsibilties:

Teaching and Learning

  • Plan, prepare, and deliver lessons at various levels of tertiary education in at least 2 of the subject matters below:

    • Machine Learning,

    • Artificial Intelligence,

    • Data Science

    • Cyber Security.

  • Provide instruction in programming languages such as C, Python, Power BI, R, Java, and Assembly Language, ensuring students develop robust coding skills.

  • Offer timely and constructive feedback on coursework, projects, and assessments.

  • Set and assess coursework and examinations

  • Moderate examination and coursework papers, ensuring standards are met.

Academic Support

  • Monitor and support students' academic progress, providing guidance on future study or career pathways.

  • Advise students on research and project work.

  • Support relevant departments in initiatives aimed at enhancing student success in technical disciplines.

  • Design and develop course materials for the relevant discipline modules, as required.

  • Serve as a Discipline Coordinator and providing academic support in relation to curriculum and assessment review.

Module and Programme Management

  • Periodically review the institution's internal programmes to ensure continued relevance and to drive continuous improvement of the curriculum.

  • Evaluate and review teaching materials to ensure adequate coverage of module and programme learning outcomes.

  • Ensure adequate adoption and quality of online teaching and learning strategies that support both face-to-face and online teaching.

  • Conduct administrative duties pertinent to the institution's programmes of study and other duties as assigned by the Head of School and/or Dean.

Additional Responsibilities

  • Contribute to departmental or institutional wide working groups or committees as assigned.

  • Adhere to quality assurance processes and ensure that quality requirements are met.

  • Participate in the school's events, marketing campaigns and projects.

  • Interact with relevant external partners as required.

  • Perform other duties/projects as assigned by the Head of School and/or Dean.

Qualifications

  • Master's Degree in related discipline. PhD candidates will be given priority consideration.

  • Candidate would ideally have a track record of academic publications.

  • Candidate would ideally have a teaching qualification (e.g. ACTA, DACE, M.Ed).

  • Candidate should hold relevant professional qualifications in at least 1 of the subject areas below:

    • Artificial Intelligence (AI), Machine Learning (ML), Data Science (DS), or Cybersecurity, preferably with certifications from EC-Council or other recognized professional bodies.

  • Candidate must have proven track record in teaching at undergraduate and/or postgraduate levels.

  • Experience or knowledge of module and/or programme leadership, development and administration within a higher education environment.

  • Candidate would ideally have a good knowledge of local higher education sector.

  • Experience in working with digital technology including an interest in emerging technology and techniques and maintaining an active interest in related developments within the sector.

  • Proficient in programming languages such as C, Python, R, Java, Assembly Language and Power BI.

  • Experience in at least 2 of the subject areas below:

    • Cyber Security, Machine Learning, Artificial Intelligence, Data Science

Other Information

  • Working Hours: Monday to Friday, 9am to 6pm.

  • Work Arrangements: Hybrid (Blend of in-office and remote work)

  • Location: Wilkie Edge


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