Explore a career at Machine Medicine
Machine Medicine Technologies (MMT) uses computer vision and computational statistics to enhance the neurological assessment of patients. Their first product, KELVIN-PD, allows motor assessments in Parkinson’s disease to be performed, recorded and used both faster and better than has ever previously been possible. KELVIN-PD is already in use at multiple clinical sites and already possesses a CE mark, being a class I medical device. MMT aims to build the platform into a generalised tool for patient selection, surgical planning and device programming for machine brain interfacing, a revolutionary therapeutic innovation. This will require the product to be built to the standards of a class III medical device.
You are an ambitious and capable PhD research scientist in computational statistics and machine learning, with a solid publication record and several years post-PhD experience in industrial or academic labs. You are conversant with the relevant branches of mathematical statistics, including Bayesian inference, MCMC and time series analysis. Previous work in a biomedical sector would be beneficial but not mandatory. You care about impact, and want to do work that matters.
SysAdmin/Devops Software Engineer
You are a hard working and talented full stack engineer with a superb command of general programming principles supplemented by a special strength in SysAdmin/DevOps. You love to build things, to see them come into existence, and to see them work beautifully. Impact matters to you and you want to build great products that positively influence the lives of millions if not billions. You are keen to join a small full stack development team (currently 2 strong) to bring scalability to our platform.
Info about MMT and the role
Machine Medicine Technologies (MMT) is a post-seed, post-revenue startup building scalable, computational systems for the analysis of clinical data, with a focus on developing a data and software layer for neuromodulation (e.g. machine-brain interfacing based therapeutics such as Deep Brain Stimulation). Currently, they provide a motor assessment platform for Parkinson’s disease, which is being used on both sides of the Atlantic at multiple clinical sites and in multiple clinical trials.
Recently MMT has been developing systems for the automatic analysis of any form of (often high dimensional) clinical data, and have been applying this approach to the problem of quality control in clinical trials. This has been productised as a SaaS service called Cato, that performs real-time monitoring of motor assessments.
The successful candidate would work on developing and deploying effective and scalable algorithms for the monitoring of clinical data in real and near-real-time (i.e. expanding and improving the functionality of Cato). These results would also be turned into high impact publications, and presented at international conferences.