Lecturer in Artificial Intelligence Education (AEP) in City of London

The Department of Informatics is looking to appoint a Lecturer in Artificial Intelligence (Academic Education Pathway). This is an exciting time to join us as we continue to grow our department and realise our vision of building a diverse, inclusive and innovative Department of Informatics at one of the most prestigious universities in the UK.

We are seeking an exceptional educator to join a multi-faculty team designing and delivering a sector-leading, fully online, interdisciplinary digital education programme: the MSc Applied Artificial Intelligence, launching in January 2027. This innovative programme will form part of a broader portfolio of interdisciplinary, AI-focused educational offerings across the university, designed to equip graduates from diverse academic and professional backgrounds with a rigorous understanding of artificial intelligence and its societal, ethical, and theoretical foundations.

The postholder will play a central role in the design, development, and delivery of high-quality, engaging online learning experiences that reflect best practice in digital pedagogy and the evolving role of AI in society. The role will contribute to teaching core conceptual and contextual topics such as the foundations and history of AI, knowledge representation, reasoning and inference, search and decision-making, research methods, and the ethical and societal implications of AI and responsible innovation. You will work collaboratively with colleagues across multiple faculties to ensure the programme is coherent, academically rigorous, and genuinely interdisciplinary.

Key responsibilities include:

• Contributing to the curriculum design, module development, and assessment strategy for the MSc Applied Artificial Intelligence.
• Delivering high-quality online teaching across areas such as reasoning and knowledge representation, search optimisation and decision-making.
• Supporting students in developing critical understanding of the history of AI and how responsible innovation is derived, research methods, and the broader implications of AI technologies across different sectors.
• Ensuring content is accessible and inclusive for a diverse global learner audience with varied academic and professional backgrounds.
• Innovating in digital pedagogy, including asynchronous and synchronous online teaching approaches, interactive content design, and online community building.
• Working as part of the multi-faculty team delivering the MSc and contributing to the wider suite of interdisciplinary AI-focused programmes.
• Contributing to scholarship in teaching and learning in AI education, consistent with the needs of the department and faculty.
• Delivering excellent student support, including acting as Personal Tutor to students on the MSc Applied Artificial Intelligence.
• Where required, undertaking enabling roles such as Senior Tutor or Assessment Sub-Board Chair, as part of the overall full-time workload allocation for the post.

This is a full-time (35 hours per week) post, and you will be offered an indefinite contract. The role works with a hybrid working pattern. While some on-site presence will be required for team collaboration, events, and programme activities, there is potential for a substantial proportion of working hours to be undertaken remotely.

To be successful in this role, we are looking for candidates to have the following skills and experience:

• Ability to teach across AI foundations and more advanced topics of AI to learners from varied academic and professional backgrounds.
• Experience of online teaching, digital learning design, or innovative pedagogical approaches (highly desirable).
• Commitment to high-quality, learner-centred education and to shaping a leading online programme in applied artificial intelligence.
• Willingness to collaborate across disciplines and contribute to a dynamic, outward-facing programme team.

Essential criteria:

• PhD in computer science, artificial intelligence or related field.
• Ability to teach at FHEQ level 7 (Master's level) across AI foundations and machine learning to learners from varied academic and professional backgrounds.
• Ability to develop and deliver high quality and innovative teaching, including teaching delivered by distance learning or online methods.
• Commitment to high quality, learner centred education and to shaping a leading online programme in applied artificial intelligence.
• Proven ability to collaborate across disciplines and contribute to a dynamic, outward facing programme team.
• Strong organisational skills, enabling management of curriculum development and delivery alongside any scholarship activity.

Desirable criteria:

• Experience of online teaching and assessments, digital learning design, or innovative pedagogical approaches (highly desirable).
• Evidence of pedagogical or education-focused scholarship outputs (e.g. publications in education journals).

The selection process will include a video presentation, an online Q&A session, and an online panel interview. Shortlisted candidates will be asked to submit a video presentation on a topic (date and topic will be provided after shortlisting). This will be reviewed by department members and will be followed by an online Q&A Sessions in the week beginning 4th May 2026. Online panel interviews are scheduled to be held in the week beginning 11th May 2026.

At King's, we believe that the diversity of our community and a culture that is welcoming, open, inclusive and collaborative, are great strengths of the university. The Equality Act of 2010 protects the rights of our students and staff and provides a framework to fulfil our duties to eliminate unlawful discrimination, harassment and victimisation and in addition, to advance equality of opportunity and foster good relations between those who share a protected characteristic and those who do not.

We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the person specification section of the job description. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

Closing date: 29 March 2026.