Supervisor: Blair Thornton (Maritime Engineering) & Jon Hare (ECS)
What? Investigate how to make machines smarter and more flexible when surveying extreme environments such as the ocean.
Why? 90% of all data that exists has been generated in the last 2 years. In built environments like homes and offices, most of the data processing needed to generate knowledge from this data takes place on remote servers, and the machine that sits in your living room or pocket doesn’t need to be smart to be useful. Extreme environments lack the energy and communication infrastructure to transfer data in this way, and so machines need to be smarter to allow sensible decisions to be made when they are needed.
How? This PhD will develop the concept of intelligence that is shared between different physical locations, where machines in extreme environments are able to prioritise, encode and communicate the most important information over the limited bandwidths available for communication, so that complex decisions can be made remotely, using more powerful computational resources or be augmented by human judgement. You will investigate how intelligence can shared between different locations, to maximise productivity and real-time awareness during deep-sea surveys.
Key skills: Engineering background, a passion for field robotics, machine learning and computer vision.
Entry Requirements A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).
Closing date: applications should be received no later than 31 August 2020 for standard admissions, but later applications may be considered depending on the funds remaining in place.
Funding: full tuition fees for EU/UK students plus for UK students, an enhanced stipend of £15,009 tax-free per annum for up to 3.5 years.
How To Apply
Applications should be made online here selecting “PhD Eng & Env (Full time)” as the programme. Please enter Blair Thornton under the proposed supervisor.