At a Glance
- Tasks: Advance 3D reconstruction methods and develop robust camera tracking pipelines.
- Company: Join SpAItial, a leader in generative AI and computer vision.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Diverse workplace committed to equal opportunity and innovation.
- Why this job: Be at the forefront of redefining how industries interact with 3D environments.
- Qualifications: PhD in computer vision and expertise in multi-view geometry required.
The predicted salary is between 63000 - 77000 £ per year.
SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality. We are moving beyond 2D pixels to build models that natively understand the physics and geometry of our world. Our mission is to redefine how industries, from robotics and AR/VR to gaming and cinema, generate and interact with physically-grounded 3D environments.
We're seeking a Research Scientist focused on 3D reconstruction. You will advance methods that recover accurate camera poses and geometry from real-world imagery, working with both classical multi-view geometry and state-of-the-art learned reconstructors. The work includes structure-from-motion, bundle adjustment, SLAM, or feed-forward reconstruction, with a focus on robustness, accuracy, and methods that hold up on diverse real-world data.
Responsibilities
- Design camera pose estimators and 3D reconstructors.
- Build robust SfM and camera tracking pipelines for a variety of input imaging sensors.
- Develop bundle adjusters and nonlinear optimizers, including non-perspective camera formulations.
- Integrate and extend SOTA feed-forward reconstructors (VGGT, DA3, Pi3).
- Advance deep multi-view stereo, learned matching, and monocular depth methods for dense geometry.
- Build evaluation metrics for pose accuracy and reconstruction quality, and drive improvements against public & internal benchmarks.
- Scale reconstruction methods to large, diverse real-world datasets while keeping them reliable and efficient.
- Collaborate with researchers to bring reconstruction advances into production systems.
Key Qualifications
- PhD in computer vision with a research focus on 3D reconstruction; publications at top venues (CVPR, ICCV, ECCV, NeurIPS).
- Deep understanding of multi-view geometry: camera models, epipolar geometry, triangulation, PnP, etc.
- Strong familiarity with SOTA deep reconstructors (VGGT, DA3, Pi3) and related areas such as deep MVS, learned matching, and monocular depth estimation.
- Hands-on experience with SfM/SLAM systems (COLMAP, ORB-SLAM) and nonlinear least-squares solvers (Ceres).
- Experience shipping production-grade 3D reconstruction systems is a strong plus.
- Strong Python and PyTorch skills.
- Comfortable debugging failure cases on challenging real-world data.
At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process.
Research Scientist - 3D Reconstruction (SfM & SLAM) in London employer: SpAItial
At SpAItial, we pride ourselves on being an innovative employer at the forefront of generative AI and computer vision. Our collaborative work culture fosters creativity and inclusivity, providing ample opportunities for professional growth and development in a dynamic field. Located in a vibrant tech hub, we offer competitive benefits and the chance to contribute to groundbreaking projects that redefine how industries interact with 3D environments.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist - 3D Reconstruction (SfM & SLAM) in London
✨Get Involved in Research Communities
Dive headfirst into the scientific research world by joining relevant communities and forums. Engage in discussions, share your insights, and even attend conferences or seminars in your field. This not only boosts your visibility but can also lead to potential job opportunities—don't forget to connect with like-minded folks!
✨Show Off Your Research Projects
Have you worked on any cool research projects? Make it easy for potential employers to see your work by creating a portfolio or a personal website. This way, when you apply for roles like the one at SpAItial, you can point them to your projects and publications, showcasing your expertise directly.
✨Utilise Professional Networks
Networking is key in scientific research. Join professional bodies or organisations related to your field. They often have job boards and resources tailored for job seekers. Make connections with professionals who may know about openings or can give you tips on landing a full-time position.
✨Keep Your Eyes on Openings & Apply Directly
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We think you need these skills to ace Research Scientist - 3D Reconstruction (SfM & SLAM) in London
Some tips for your application 🫡
Highlight Your Research Experience:When applying for a full-time role in scientific research, make sure to emphasise your research experience prominently in your CV. Share specific projects you’ve worked on, the methodologies you used, and any significant findings. If you’ve published papers or presented at conferences, definitely include that too – it shows you’re on it in the academic world!
Tailor Your Cover Letter to the Research Area:Your cover letter should reflect your passion for the specific area of research at SpAItial. Mention relevant experiences that align with the organisation’s goals or projects. This shows that you’ve done your homework and are genuinely interested in the position – plus, it helps us see how you’d fit into the team dynamics.
Showcase Your Data Analysis Skills:In scientific research, data analysis skills are a big deal! Make sure to detail any relevant analytical tools or software you’re familiar with, like R, Python, or statistical packages. Employers are keen to know you can handle the data-heavy elements of the role, so add specific examples where you’ve used these skills effectively.
Discuss Your Future Research Goals:In your motivation section, it’s a great idea to talk about your future research goals and how they align with the work being done at SpAItial. This shows that you’re not just looking for any job, but rather a chance to contribute meaningfully to the field. We love to see applicants who are forward-thinking and enthusiastic about their research journey!
How to prepare for a job interview at SpAItial
✨Showcase Your Research Skills
In scientific research, it’s crucial to demonstrate your ability to design and conduct experiments. Come armed with examples of past projects where you've developed hypotheses, collected data, and analysed results. Be ready to discuss any specific methodologies or tools you’ve used, like PCR techniques or statistical software.
✨Prepare for Technical Questions
Expect some technical questions specific to your field. Make sure you're up to speed with recent advancements in scientific research related to the role at SpAItial. Brush up on concepts relevant to their projects and be prepared to discuss how you would approach a specific research problem or challenge they might face.
✨Know Your Publications
If you've authored or co-authored any papers, be prepared to discuss them! Highlighting your contributions to published research can really set you apart. It shows not only your expertise but also your ability to communicate complex ideas clearly, which is key in scientific research roles.
✨Exhibit Your Team Spirit
In full-time roles, collaboration is often at the heart of scientific research. Prepare examples that show how you've successfully worked in teams, dealt with conflicts, or contributed to group projects. We want to know how you can work effectively with the team at SpAItial to drive research projects forward.
