Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Research Associate in Computer Vision

University of Oxford
Oxford
1 month ago
Applications closed

Related Jobs

View all jobs

Research Assistant/Associate in Data Science for Construction Productivity (Fixed Term)

Research Assistant/Associate in Data Science for Construction Productivity (Fixed Term)

Machine Learning Researcher

Machine Learning Researcher

Research Associate Deep learning and Fetal Neurosonography

64950 - Data Analyst

Computer Science - Wolfson Building, Parks Road, Oxford We are excited to offer this Research Associate position at the University of Oxford, under the supervision of Professor Ronald Clark. The post holder will join the Perceptual Intelligence and Extended Reality Lab (PIXL) to work on an ARIA-funded project at the intersection of Computer Vision and Climate Science. In this project we are developing a new approach for estimating a dynamic, four-dimensional digital twin of the atmosphere using a ground-based array of stereo cameras and sensors. The post-holder will contribute across the research lifecycle from dataset curation to the design of novel computer vision models. Flexible working This post is based at the Department of Computer Science and on-site working is required. Remote working is possible in agreement with the PI. This post is based at the Department of Computer Science and on-site working is required. Remote working can be possible in agreement with Professor Ronald Clark. What We Offer As an employer, we genuinely care about our employees’ wellbeing and this is reflected in the range of benefits that we offer including: • An excellent contributory pension scheme
• 38 days annual leave (pro-rata for part-time jobs)
• A comprehensive range of childcare services
• Family leave schemes
• Cycle loan scheme
• Discounted bus travel and Season Ticket travel loans
• Membership to a variety of social and sports clubs Diversity
Committed to equality and valuing diversity. Application Process

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 Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.