Lecturer in AI, School of Computer Science and Electronic Engineering

University of Essex; Colchester; On-site; GBP 40,000 - 60,000; Full time

Job summary

A leading academic institution in the UK seeks an academic to join their Artificial Intelligence Research Group. The role involves conducting research in areas such as Generative AI and Natural Language Processing, as well as teaching across undergraduate and postgraduate modules. The ideal candidate will have a doctoral degree and a proven track record in teaching and research. This position supports a diverse and inclusive environment, aiming to advance AI research and education.

Qualifications

• Proven experience in teaching at undergraduate and/or postgraduate levels.
• Experience in designing and planning learning activities.
• Strong written and verbal communication skills.

Responsibilities

• Contribute to cutting-edge research and high-quality teaching in AI.
• Secure research funding and publish in leading venues.
• Teach undergraduate and/or postgraduate modules.

Skills

Strong research capabilities

Teaching experience

Communication skills

Education

Doctoral-level research degree in Computer Science or related field

Job description

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.

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*

The University of Essex is a campus based University and all academic appointments are made with the expectation that you will be present on campus to fulfil the requirements of your position. At the time of a job offer, the possibility of hybrid working, will be discussed and considered on an individual basis, but you will be required to be based within the UK.

At the University of Essex, internationalism and diversity is central to who we are and what we do. We are committed to being a cosmopolitan, internationally oriented university that is welcoming to staff and students from all countries, faiths and backgrounds, where you can find the world in one place.

Please see the attached job pack, which contains a full job description and person specification which outlines the full duties, skills, qualifications and experience needed for this role plus more information relating to the post. We recommend you read this information carefully before making an application. Applications should be made on-line, but if you would like advice or help in making an application, or need information in a different format, please contact [e-mail]

*More information: Working at the University