Lecturer/Associate Professor in Robotics & AI

UCL Eastman Dental Institute
London
1 year ago
Applications closed

Related Jobs

View all jobs

Teaching Associate - Data Science / Statistics

Lecturer in Artificial Intelligence (2 roles)

Lecturer in Digital Innovation and Artificial Intelligence

Faculty Fellowship Programme - Data Science - May 2026

About the role

Our vision for Robotics at UCL East Campus is to set up a new robotics powerhouse at UCL. To support our vision, over the next few years, we will be hiring more than 20 research and teaching staff in robotics. The positions advertised here is part of this strategy. To provide world-class facilities at UCL East Campus for research and teaching in Robotics & AI, we are seeking to fill a Lecturer/Associate Professor post in Robotics and AI. Areas that we aim at covering: Machine Learning in Robotics.

Appointment at Lecturer (Grade 8) or Associate Professor (Grade 9) level will be determined by depth of experience and track record. For Grade 9, you will show sustained and repeated contributions to the subject area or body of knowledge, and a sustained publication record, which demonstrates the potential to produce significant contributions to the discipline. All research outputs are available through Open Access wherever possible. You will demonstrate widespread connections across national and/or international subject community, including active collaborations/contact with leading figures in subject area; regular collegiate engagement with colleagues from distinct disciplines on cross-disciplinary issues; network of collaborators or advice-seekers in industry, healthcare, or policy organisations (or similar, depending on discipline context); contacts and networks both domestic and international. You would be expected to demonstrate sustained excellence in all aspects of academic life.

The main purpose of this new role is to support the growth of the Computer Science Department and the Robotics & AI area through conducting research, teaching, outreach, and entrepreneurial activities in areas related to robotics and AI. The role also encompasses being a mentor and a point of contact for emerging talent and support the EDI activities in the department.

About you

For this role, you will need to:
1. To carry out research and produce publications, or other research outputs, in line with personal objectives agreed in the Staff review process.
2. To obtain research funding support.
3. To engage with the broader scholarly and professional communities.
4. To teach modules in support of our new master's programmes (MEng/MSc in Robotics and AI), and to support other undergraduate and graduate level teaching programmes at UCL Computer Science and the Faculty of Engineering, as allocated by the Dean of Engineering and relevant Heads of Department.
5. To supervise or assist with supervision of undergraduate, taught graduate (Masters) or research graduate (MPhil/MRes/PhD/EngD) students.
6. To contribute to the development, planning and implementation of a high-quality curriculum.
7. To participate in the development, administration and marking of exams and other assessments.
8. To provide pastoral care and support to students.
9. To participate in the administration of the Computer Science Department and department’s programmes of study and other activities as requested.
10. Actively promote UCL East’s academic values of interdisciplinarity, collaboration, and public engagement.
11. To support and advance UCL’s Equity, Diversity, and Inclusion ambitions.

What we offer

Salary range:
Lecturer - £52, to £61, including London Allowance
Associate Professor - £66, to £72, including London Allowance

As well as the exciting opportunities this role presents, we also offer some great benefits such as: 41 days holiday including bank holidays, hybrid working, pension scheme, cycle to work scheme and season ticket loan. On-Site nursery, On-site gym. Enhanced maternity, paternity and adoption pay. Employee assistance programme: Staff Support Service, Discounted medical insurance.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.