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For Companies At a Glance
- Tasks: Design and build models predicting human attention in complex visual environments.
- Company: Exciting startup focused on human attention and spatial AI.
- Benefits: Competitive salary, equity options, and remote-first work culture.
- Other info: Dynamic startup environment with opportunities for impactful research.
- Why this job: Join as a founding member and shape the future of AI research.
- Qualifications: PhD in relevant field and strong Python skills required.
The predicted salary is between 60000 - 75000 ÂŁ per year.
Location: UK‑based, remote‑first (occasional London visits, 1 day a month)
Employment type: Full‑time
Salary: £60,000–£75,000 base
Equity: 0.1%–3.0% options
Visa sponsorship: Not available (UK Graduate Visa accepted)
Role overview
We are helping a small startup hire a Research Scientist to work on applied research at the intersection of human attention, perception and spatial AI. Founding style role, join as their 3rd hire! The role focuses on building models that predict, interpret and simulate how people attend to and interact with complex visual and spatial environments. You will work on real‑world problems that connect machine learning, computer vision and cognitive modelling, with a strong emphasis on hands‑on experimentation and practical impact. This position is well suited to researchers interested in spatial AI, embodied AI, XR/VR, simulation, automotive systems, robotics or interactive 3D environments. Prior experience across all of these areas is not required.
What you will work on
- You will help design and build models that reason about where people look, what they notice and how attention changes with task, context, motion, layout and semantics.
- Example work includes:
- Predicting human attention and gaze in 2D and 3D scenes
- Modelling attention during search, navigation, inspection and decision‑making
- Connecting attention with language, goals, objects and scene context using multimodal models
- Inferring human intent or priorities from gaze, movement and interaction data
- Developing evaluation frameworks for human‑like perception
- Adapting foundation models for spatial and human‑centred AI tasks
- Working with synthetic and real‑world data such as images, video, depth, 3D scenes, gaze and interaction logs
- Collaborating with engineers to move research prototypes towards robust systems
Responsibilities
- In this role, you will:
- Develop machine learning models for attention, perception, behaviour or intent prediction
- Design experiments, baselines, metrics and validation protocols
- Train and evaluate models using visual, spatial, temporal and multimodal data
- Read, reproduce and extend relevant research
- Work with 2D and 3D data representations including images, video, depth, point clouds and simulated environments
- Communicate research decisions clearly through notes, demos, presentations and code
- Contribute to research direction and technical roadmap
Essential requirements
- PhD in a relevant field (e.g. machine learning, computer vision, robotics, HCI, cognitive science, neuroscience or graphics)
- Strong research track record (top‑tier publications, patents or substantial open‑source work)
- Hands‑on deep learning experience
- Strong Python skills and experience with PyTorch
- Ability to independently design, run and evaluate ML experiments
- Experience working with complex datasets and rigorous evaluation
- Genuine interest in human attention, perception or behaviour
- Clear communication skills and comfort working in a small, fast‑moving team
Useful experience (not required)
- Human attention, gaze modelling, visual saliency or cognitive modelling
- 3D computer vision, spatial AI, simulation, XR/VR or robotics
- Multimodal or temporal modelling
- Egocentric video, eye‑tracking or behavioural data
- Foundation model fine‑tuning or evaluation
- Research engineering and reproducible ML pipelines
You are likely to enjoy this role if you:
- Are curious about how humans perceive and interact with the world
- Are comfortable with ambiguity and open‑ended research problems
- Are technically strong and able to build and debug your own models
- Care about rigour, evaluation and evidence
- Enjoy working in a startup‑style, research‑led environment
- Want to turn research ideas into real systems
Founding Research Scientist - Human Computer Vision in Portsmouth employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Research Scientist - Human Computer Vision in Portsmouth
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend relevant meetups or conferences, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to human attention, perception, and spatial AI. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and being ready to discuss your research. Practice explaining complex concepts in simple terms, as communication is key in a small, fast-moving team.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission at StudySmarter.
We think you need these skills to ace Founding Research Scientist - Human Computer Vision in Portsmouth
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for human attention and spatial AI shine through. We want to see that you're genuinely excited about the intersection of these fields and how they can impact real-world problems.
Tailor Your CV: Make sure your CV highlights relevant experience, especially in machine learning, computer vision, or cognitive science. We love seeing how your background aligns with our needs, so don’t be shy about showcasing your top-tier publications or projects!
Be Clear and Concise: In your written application, clarity is key! Use straightforward language to explain your research and technical skills. We appreciate a well-structured application that makes it easy for us to understand your expertise and potential fit.
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 this exciting opportunity as our founding research scientist!
How to prepare for a job interview at Harnham
✨Know Your Stuff
Make sure you brush up on the latest research in human attention, perception, and spatial AI. Familiarise yourself with key concepts and recent advancements in machine learning and computer vision. This will not only help you answer technical questions but also show your genuine interest in the field.
✨Showcase Your Experience
Prepare to discuss your past projects and how they relate to the role. Highlight any hands-on experience you've had with deep learning, Python, or working with complex datasets. Be ready to explain your thought process and the impact of your work, as this will demonstrate your ability to contribute to their research direction.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's research goals, team dynamics, and how they envision the role evolving. This shows that you're not just interested in the job, but also in how you can fit into their vision and contribute meaningfully.
✨Communicate Clearly
Since clear communication is essential in a small team, practice explaining complex ideas in simple terms. Whether it's discussing your research or presenting your findings, being able to articulate your thoughts clearly will set you apart from other candidates.