Researcher for Textile Analysis and Manipulation

Kingston University

Kingston upon Thames

1 year ago

Applications closed

Related Jobs

View all jobs

Machine Learning Researcher Statistics Python AI...

Machine Learning Researcher Statistics Python AI

Machine Learning Researcher Statistics Python AI - Client Server

Senior Quantitative Researcher — Deep Learning for Markets

Computer Vision Scientist - Darcie Talent

Machine Learning Researcher

The Role

We are currently seeking a highly motivated and skilled researcher to join our dynamic team in the field of Artificial Intelligence (AI) and Immersive Technologies.

As a Researcher in AI, computer vision and robotics, you will be actively involved in advancing textile manipulation through cutting-edge robotics, deep learning, and computer vision. The focus of this position is on developing innovative approaches for robotic cloth folding, unfolding, and handling tasks. Using state-of-the-art techniques such as reinforcement learning, neural networks, and real-time visual recognition, you will contribute to new solutions in automation for textile processing, bringing our project’s vision closer to real-world application.

The Person

You will have a PhD or Master’s degree in Robotics, Computer Science, Engineering, or a related field, with a focus on machine learning, computer vision, or robotic manipulation.

You will also have proven experience in deep learning frameworks (e.g., TensorFlow, PyTorch) and computer vision tools with a strong knowledge of reinforcement learning and practical experience with robotic systems.

You will have excellent academic writing skills demonstrated through publications in reputable conferences/journals and have the ability to work collaboratively in a team and lead research initiatives.

The Faculty

The Faculty of Engineering, Computing & the Environment (ECE) is among the most diverse in the UK, offering a wide range of subjects that encourage cross-discipline innovation. Our academics are experts, deeply engaged in research, which they bring into their teaching. Our state-of-the-art facilities include specialised labs, a public outreach centre, a virtual reality centre, a rocket lab, flight and race simulators, a renewable energy lab, automotive and mechanical labs and new labs dedicated to electrical, electronic, and robotic engineering, along with an advanced design studio. This combination creates an ideal environment for practical learning for future engineers, and an exciting atmosphere for academic professionals.

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

Industry Insights

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

Jan 24, 2026

Education

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

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Jan 18, 2026

Careers Jobs

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jan 13, 2026

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.