London, UK /
Technical roles /
Detect Alzheimer’s disease 20 years early through speech-based algorithms
Alzheimer’s disease and other dementias will affect 1 in 3 people, causing progressive loss of memory – loss of what makes us who we are. No disease modifying treatment currently exists. We now know that the disease progresses silently for decades before symptoms become obvious and a diagnosis is made, which is a major reason why treatments don’t work. But very subtle changes do exist in the silent stages – in episodic memory, executive function, and language – and, with sophisticated enough technology, these changes can be detected in the way someone speaks.
Novoic is a clinical stage biotechnology company developing algorithms to detect neurological diseases such Alzheimer’s disease in their preclinical stages, by analysing audio-linguistic patterns of speech. Building on decades of research, the company is currently testing these algorithms in the clinic, to validate them as software-as-a-medical-device, and bring the first clinically viable speech-based algorithms to market. The company is venture capital funded, working with the Alzheimer’s Drug Discovery Foundation and Gates Ventures to develop a global standard for speech biomarkers, and is the only speech company to have been backed by the UK NHS’ AI organisation to test out its algorithms in 5 common neurological indications.
Founded by Oxford and Cambridge researchers, our team is a reflection of the pioneering nature of our work. Physicians, clinicians, and neuroscientists work side-by-side with machine learning researchers and software engineers, all united by a mission to help patients and their families through early, non-invasive diagnosis.
Why we need you now
Through our ongoing clinical programs, we are collecting what we believe to be the best clinical speech datasets for training models to detect neurological disease, in terms of the study design, the speech tasks and the scale of the data. This puts us in a unique position to develop the first speech-based diagnostic tests that can be integrated into the clinic and actually work. But this data is only useful if we can develop models that take advantage of it. Once our next clinical study concludes, we will be able to answer some of the biggest outstanding research questions in the field but we’ll be limited by capacity, so we urgently need talented researchers and engineers to help us.
What will you actually do
- Reading, analysing and criticising papers in fields such as representation learning, NLP and speech processing.
- Participating in brainstorming sessions and research meetings with our team and external advisors, where we discuss and challenge each other’s ideas.
- Training large-scale deep learning models and thinking deeply about why they might be making the predictions that they are making.
- Developing our internal and open-source packages. For example, take a look at our GitHub repos.
- Writing production code to serve our trained models on the cloud.
Who are you
- 1+ years of experience working with deep learning models in industry and/or academia.
- Passionate about machine learning. You love reading papers, blog posts, talking about the latest trends or discussing ideas in front of a whiteboard.
- A great engineer, capable of writing code in Python and one of PyTorch, TensorFlow, or another deep learning framework.
- Excited about being part of a small, quickly growing startup. You want to be a part of our ambitious project. You do not mind the uncertainty that comes with early stage startups.
- Working in healthcare is something that excites you.
- Competitive salary and equity options arrangement.
- 28 days of paid holiday.
- Flexible working arrangements, including hybrid remote work policy.
- A deep sense of meaning, having a significant role in changing the way brain diseases are diagnosed, improving the lives of millions.
- High degree of responsibility and the opportunity to grow into a senior role as the company scales.
- Personal development plan and half a day per week to work on your own projects.
- Authorship on high-impact papers.
- Paid attendance at top machine learning conferences.