At a Glance
- Tasks: Join a cutting-edge project in Computer Vision and Climate Science at Oxford.
- Company: Be part of the prestigious University of Oxford, renowned for its research excellence.
- Benefits: Enjoy 38 days annual leave, a pension scheme, and various corporate perks.
- Other info: Remote work may be possible; applications must reflect personal insights.
- Why this job: Contribute to impactful research while working in a diverse and innovative environment.
- Qualifications: Ideal for those with a background in computer vision or related fields.
The predicted salary is between 38674 - 46913 £ per year.
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.
Location and Working Arrangements:
This post is based at the Department of Computer Science, University of Oxford. On-site working is required, but remote working may be possible in agreement with the PI.
What We Offer:
- 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 various social and sports clubs
Diversity: We are committed to equality and valuing diversity.
Application Process:
Applicants are required to upload an up-to-date CV and a supporting statement demonstrating how they meet each of the essential criteria listed in the job description. Applications lacking a supporting statement or CV, or not addressing the criteria in sufficient detail, will not be considered.
While AI tools can assist in application preparation, submissions that are clearly AI-generated without personalisation or insight will be rejected. Your application should reflect your own experiences and understanding of the role.
The closing date for applications is noon on 9th September 2025. Interviews are expected to be held in September.
Contact Person: HR Coordinator
Vacancy ID: 180878
Contact Phone: [not provided]
Closing Date & Time: 09-Sep-2025 12:00
Pay Scale: RESEARCH GRADE 7; Grade 07RS: £38,674-£46,913 per annum; Grade 06RS: £34,982-£40,855 per annum (inclusive of Oxford University weighting)
#J-18808-LjbffrResearch Associate in Computer Vision employer: University of Oxford
The University of Oxford is an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration within the Perceptual Intelligence and Extended Reality Lab. Employees benefit from generous annual leave, a comprehensive pension scheme, and opportunities for professional growth in a prestigious academic environment, all while contributing to impactful research at the intersection of technology and climate science.
StudySmarter Expert Advice🤫
We think this is how you could land Research Associate in Computer Vision
✨Tip Number 1
Familiarise yourself with the latest advancements in computer vision and climate science. This will not only help you understand the project better but also allow you to engage in meaningful discussions during interviews.
✨Tip Number 2
Network with professionals in the field by attending relevant conferences or workshops. Making connections can provide insights into the role and may even lead to recommendations.
✨Tip Number 3
Prepare to discuss your previous research experiences in detail, especially those related to dataset curation and model design. Be ready to explain how these experiences align with the responsibilities of the position.
✨Tip Number 4
Stay updated on the specific technologies and tools used in the PIXL lab. Demonstrating knowledge of their methodologies during the interview can set you apart from other candidates.
We think you need these skills to ace Research Associate in Computer Vision
Some tips for your application 🫡
Understand the Role:Read the job description thoroughly to grasp the essential criteria and responsibilities. Make sure you understand the intersection of Computer Vision and Climate Science, as this is crucial for your application.
Craft a Tailored Supporting Statement:Your supporting statement should directly address each of the essential criteria listed in the job description. Use specific examples from your experience that demonstrate your skills and knowledge relevant to the role.
Update Your CV:Ensure your CV is current and highlights relevant experience, particularly in research, dataset curation, and computer vision models. Tailor it to reflect the skills and experiences that align with the position.
Personalise Your Application:Avoid using generic templates or AI-generated content. Your application should reflect your personal insights and experiences. This will help you stand out and show genuine interest in the position.
How to prepare for a job interview at University of Oxford
✨Understand the Project
Familiarise yourself with the ARIA-funded project and its goals. Be prepared to discuss how your skills in computer vision can contribute to developing a dynamic digital twin of the atmosphere.
✨Showcase Relevant Experience
Highlight your previous work related to dataset curation and computer vision models. Use specific examples to demonstrate your expertise and how it aligns with the role.
✨Prepare Thoughtful Questions
Think of insightful questions to ask during the interview. This shows your genuine interest in the position and helps you understand the expectations and culture of the lab.
✨Personalise Your Application
Ensure your CV and supporting statement reflect your personal experiences and insights. Avoid generic responses and tailor your application to address the essential criteria outlined in the job description.
