You will join a small team of researchers and software/hardware engineers, as a member of which you will
- Apply your knowledge and understanding of probabilistic machine learning to the task of solving difficult problems involving
object selection, tracking and recognition in complex dynamic visual scenes, using inspiration from the architecture
and function of visual processing in the brain
- Develop the best way of mapping the algorithms onto a neuromorphic, massively parallel, asynchronous, many-core hardware
platform, which will optimise the speed and energy requirements of processing
- Design experiments to demonstrate the performance of the system, initially as a proof of concept and leading on to a
minimum viable product
- Prepare written and verbal accounts of your work for both internal and external, conference presentations, and document
your work in a form necessary for patent application
- Maintain your awareness and knowledge in the field of machine intelligence, in probabilistic machine learning and
knowledge representation, and in the neuroscientific principles underlying our neuromorphic software/hardware approach
- Share your knowledge and understanding with other team members and be receptive to and proactive in the development
of novel ideas and approaches which will help us to meet our goals.
What we expect from you
Ideally you will possess as many of the following attributes as possible:
- A PhD (or equivalent demonstrable research training and experience) in the area of probabilistic
machine learning, preferably but not necessarily in the context machine vision, and ideally
in the field on dynamic visual motion analysis and processing
- A sound understanding of the mathematical principles underlying probabilistic machine learning
- Background knowledge of the architecture and function of visual information processing in the brain
- A formal training and/or experience in either computer science, engineering or mathematics at bachelor degree
level, ideally graduating at a first class or upper second level or equivalent
- the necessary programming skills to turn your ideas and inventions into working algorithms.
This could initially be through implementation in Matlab, but you should also be willing to gain
sufficient C/Python programming skills necessary to work with our software engineers on
implementation of your algorithms on our event-based many-core neuromorphic hardware.
The opportunity exists for an enthusiastic, proactive person who shares our goals and ambitions,
to take a defining and formative role in our early-stage company. You will be encouraged to
develop your role in a way which will allow your level of influence and responsibility in the
company to rapidly grow as we build our technology, products and team over the next few years.
Bridgeworks, 67-69 Bridge Street, Manchester, M3 3BQ, UK
Email us a copy of your CV to: firstname.lastname@example.org