Research Assistant or Research Associate in Robot Learning and Fast Recovery

Imperial College London
London
1 year ago
Applications closed

Related Jobs

View all jobs

Research Assistant/Associate in Cardiac Computational Modelling via Machine Learning and Biomechanics Simulations

Postdoctoral Research Assistant in optical neural networks (experiment)

Postdoctoral Research Associate in Statistical Genetics and Machine Learning (Fixed Term)

Postdoctoral Research Associate in Statistical Genetics and Machine Learning (Fixed Term)

Postdoctoral Research Associate in Statistical Genetics and Machine Learning (Fixed Term)

Machine Learning Engineer

The Adaptive and Intelligent Robotics Lab (AIRL) in the Department of Computing at Imperial College London is seeking a talented Research Associate (post-doc) or Research Assistant (pre-doc) to work on a new project called TRUSTLINE, which is part of the Learning Introspective Control (LINC) DARPA Program. The project aims to develop machine learning (ML)--based introspection and monitoring technologies that enable robotic systems and critical infrastructures to detect and understand ongoing situations as they encounter uncertainty or unexpected events. The program also seeks to develop technologies to communicate these changes to a human or AI operator while retaining operator confidence and ensuring continuity of operations. The successful applicant will focus on developing and testing new methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under-actuated large-scale manipulators (., container cranes).

For further information on Dr Antoine Cully’s research and projects, see


This project will be achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. Familiarity with existing methods from these domains, such as Quality-Diversity algorithms, reinforcement learning, model predictive control, parallel computing using JAX and rapid online learning, is highly desirable, but candidates demonstrating an ability and willingness to become familiar with these topics and able to contribute to them will also be considered. This project has a strong emphasis on applications on physical robots, experience and appetite to face the challenge of applying learning algorithms on physical robots are therefore required. One of the goals of this project is to commercialise the developed technology. Therefore, an entrepreneurial mindset and willingness to take challenges is a plus.


You must have a strong computer science background and have experience in one or more of the following areas: Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record.

You should also have:

Research Associate: A PhD (or equivalent) in an area pertinent to the subject area, . Computer Science, Machine Learning, Robotics. Research Assistant: A Master’s degree (or equivalent) in an area pertinent to the subject area, . Computer Science, Machine Learning, Robotics. A strong background in both robotics and/or machine learning, including experience conducting experiments on physical robots. Excellent programming skills are required and strong experience with the Python library JAX would be a plus. Excellent communication skills and the ability to organise your own work and prioritise work to meet deadlines. Experience writing and publishing academic papers.

Please see job description for a full list of requirements.

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant, salary range £43,003 - £46,297 per annum.


The opportunity to continue your career at a world-leading institution Sector-leading salary and remuneration package (including 38 days off a year)

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.

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.