Lecturer in AI

The School of Computer Science and Electronic Engineering (CSEE) at the University of Essex is a dynamic and internationally recognised department within the Faculty of Science and Health. We are known for our world-class research and our commitment to delivering an outstanding educational experience.

Essex has a distinguished history in Artificial Intelligence (AI) and Communications, being one of the first UK universities to establish a central AI research hub and to pioneer a systems approach to telecommunications. Since 2014, CSEE has undergone significant expansion, building on its foundational strengths to develop new areas of excellence. This growth has led to the formation of four thriving research groups:

1. AI – Artificial Intelligence
2. BCI-NE – Brain-Computer Interfaces & Neural Engineering
3. COMNET – Communications & Networking
4. RES – Robotics & Embedded Systems

We are now seeking a talented academic to join the Artificial Intelligence Research Group. The successful candidate will contribute to cutting-edge research and high-quality teaching in areas such as Generative AI, Large Language Models (LLMs), Natural Language Processing, and Computer Vision. They will be expected to secure research funding, publish in leading venues, and contribute to the School’s academic leadership and international profile.

Teaching responsibilities will include undergraduate and/or postgraduate modules, with opportunities to develop new content aligned with the candidate’s expertise. We are particularly interested in candidates who can demonstrate strong research and teaching capabilities in one or more of the following areas:

• Foundations and Explainability in Machine Learning – including theoretical underpinnings of learning algorithms, model interpretability, fairness, robustness, and methods for transparent and accountable AI systems.
• Theoretical Foundations of Artificial Intelligence – encompassing formal models of learning and reasoning, algorithmic complexity, statistical learning theory, and the mathematical principles underpinning modern AI systems.
• Generative AI and Foundation Models – including model architecture, training efficiency, safety, and evaluation of large-scale generative systems.
• Multimodal Large Language Models (MLLMs) – with a focus on integrating vision, language, and audio for tasks such as visual question answering, image captioning, and embodied AI.
• Natural Language Processing (NLP) – especially in areas such as low-resource language modelling, dialogue systems, prompt engineering, and explainability.

This is an exciting opportunity to join a forward-thinking department that values innovation, collaboration, and impact. We welcome applicants who are passionate about advancing AI research and education in a supportive and ambitious academic environment.

We are committed to fostering an inclusive and equitable environment by actively supporting the representation, empowerment, and opportunities for women and non-binary individuals, ensuring their voices are heard, their contributions are valued, and their potential is recognised within the School.

A full list of duties and responsibilities can be found within the job pack.

Please note, the successful candidate will be appointed to the post of Lecturer.

Qualifications and Skills required

You will hold a a doctoral-level research degree in a relevant discipline (e.g, Computer Science, Artificial Intelligence, or a closely related field), or equivalent professional experience and standing in the field and Fellowship of the Higher Education Academy, or the ability to gain professional recognition at this or a higher level if appropriate.

You will also have proven experience in teaching at undergraduate and/or postgraduate levels, or demonstrable potential to achieve this, as well as experience of designing and planning of learning activities and of developing effective learning environments (face-to-face and/or virtual learning). You will possess strong written and verbal communication skills.

*Previous applicants need not apply*

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