Dognosis
At Dognosis, we’re building the future of canine neuroscience and cancer detection using biosensors, embedded systems, and real-time data tools. Our work involves everything from EEG helmets for dogs to robotic breath sampling devices, and at the heart of it all is the data - physiological, behavioural, neural. As a Frontend Engineering Intern, you’ll help design and build the tools that researchers and engineers use to make sense of this data. Your work will make it easier to spot patterns, troubleshoot systems, and run complex experiments with more confidence and clarity.
You’ll help create dashboards, visualisations, and annotation tools that bring real-time sensor streams to life. These might include multi-channel EEG signals, motion data, or breath analytics from our olfaction systems. Most of the interfaces will be built in React (or a similar framework), and many will involve integrating live data, stream syncing, or scientific charts. There’s plenty of room for creativity, from shaping our design system to building quick internal tools for debugging or insight generation. We’re looking for someone excited by the challenge of turning complex, unfamiliar systems into clear, intuitive interfaces that make people’s work easier and better.
You should have some experience building frontends, whether through personal projects, internships, or coursework, and a working comfort with JavaScript and a modern framework like React or Vue. This isn’t a senior role, so we don’t expect mastery, but you should be able to take a component from sketch to code and debug it when something breaks. If you’ve built tools that visualise real-time data, worked with sensor streams, or created something for research or engineering teams, that’s a great bonus, but it’s not a requirement. What matters most is that you’re curious, eager to learn, and comfortable getting your hands dirty with unfamiliar problems.
We’re especially excited to meet people who enjoy working across disciplines, whether that’s syncing up with a backend engineer, collaborating with someone from the hardware team, or adapting your UI based on feedback from a neuroscientist. Familiarity with libraries like D3, Plotly, or Tailwind will help, but again, we don’t expect you to know it all. What we care about is that you ask good questions, think clearly, and want to build tools that make complex systems easier to understand. If you’re thoughtful, hands-on, and excited about using frontend engineering to support real-world science, you’ll feel right at home here.