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- Tasks: Design and optimise algorithms for cutting-edge computer vision projects.
- Company: Join a world-class research team in a dynamic R&D environment.
- Benefits: Competitive salary, equity package, and access to high-performance computing.
- Why this job: Make significant contributions to the field and attend top-tier conferences.
- Qualifications: PhD in Computer Vision or related field with strong research background.
- Other info: Collaborative environment focused on innovation and real-world impact.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a PhD Computer Vision Scientist with deep expertise in object detection, tracking, or related visual perception tasks. You’ll join our world-class research team to design, implement, and optimize algorithms that advance the state of the art in dynamic scene understanding. This role is ideal for a researcher who has already made significant contributions to the field, for example, through publications at top-tier venues such as CVPR, ICCV, or ECCV and is eager to apply that experience in a fast-paced, applied R&D environment.
Requirements
- PhD in Computer Vision, Machine Learning, Robotics, or a related field.
- Strong research background in object detection, tracking, segmentation, or visual understanding, VLM's, VLA's.
- Proven record of publications in CVPR, ICCV, ECCV, or comparable conferences.
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- 1-3 years industry experience.
What We Offer
- Competitive salary and equity package.
- Access to high-performance computing infrastructure.
- Opportunities for publication, collaboration, and attending top-tier conferences.
- A collaborative, research-driven environment with a focus on innovation and impact.
Computer scientist (f/m/d) in London employer: Darcie Talent
Contact Detail:
Darcie Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computer scientist (f/m/d) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the computer vision field, attend meetups, and engage in online forums. You never know who might have a lead on that perfect job!
✨Tip Number 2
Show off your work! Create a portfolio showcasing your projects, publications, and any cool algorithms you've developed. This will help you stand out when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and being ready to discuss your research in detail. Practice explaining complex concepts in simple terms – it’s all about making a connection!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes the process smoother for everyone involved.
We think you need these skills to ace Computer scientist (f/m/d) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in computer vision, object detection, and any publications you've got. We want to see how your background aligns with our needs, so don’t hold back on showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about the role and how your expertise can contribute to our research team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects: If you’ve worked on any cool projects or research, make sure to mention them! Whether it’s a paper published at CVPR or a project using PyTorch, we want to know what you’ve done and how it relates to the work we do at StudySmarter.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values!
How to prepare for a job interview at Darcie Talent
✨Know Your Research Inside Out
Make sure you can discuss your previous work and publications in detail. Be prepared to explain the methodologies you used, the challenges you faced, and how your contributions have advanced the field of computer vision.
✨Brush Up on Technical Skills
Since the role requires proficiency in Python and deep learning frameworks like PyTorch or TensorFlow, ensure you're comfortable coding on the spot. Practise common algorithms related to object detection and tracking, as you might be asked to solve problems during the interview.
✨Familiarise Yourself with the Company’s Work
Research the company’s projects and recent publications. Understanding their focus areas will help you tailor your responses and show genuine interest in how you can contribute to their goals.
✨Prepare Thoughtful Questions
Have a list of insightful questions ready to ask your interviewers. This could include inquiries about their current research challenges or how they envision the future of dynamic scene understanding. It shows that you’re engaged and thinking critically about the role.