Applied Sciences & Professions, Business & Management, Education & Training, Engineering & Technology, Medicine & Health
Fully Funded
Europe, United Kingdom (UK) (England, Northern Ireland, Scotland and Wales)
Description
Staffordshire University is pleased to announce a 3-year fully funded PhD scholarship in the School of Computing and Digital Technologies, to commence in January 2021 or April 2021. ِApplicant will be expected to take up to 250 hours of teaching or teaching related activities per academic year in the School of Computing and Digital Technologies. This is also an excellent opportunity to develop your academic portfolio with HE teaching experience and benefit from the University’s training programmes. The posts are located on the Stoke-On-Trent campus.
Applications are invited for a 3-year fully funded PhD scholarship in the area of Adaptive Neural Networks.
Machine Learning solutions are critically dependent of their training. Neural Networks can only perform a specifically defined task and are unable to learn a process or a function that evolve in context. To solve these context changing problems, different techniques have been proposed but they still fall short in a number of aspects. Neuroevolution is one of the most promising methods, which constitutes a general and effective method that can be applied to a wide range of problems. It presents several advantages with respect to alternative training methods for neural networks. Therefore, more work needs to be done to improve adaptation of current neural networks models including Neuroevolution methods, so that they can adapt and evolve in context. During your PhD project, you will explore relevant solutions and develop and experiment with new adaptive models, which will be tested on relevant benchmarks and some real-world applications such as healthcare, games and finance.
Opportunity Focus Areas:
– Computer Science
– Digital Technology
– Deep Learning
– Neuroscience
-Programming
Specialities
Details
More than year
ELIGIBILITIES
25 - 35, 36 - 60
Male, Female
Benefits
Required Documents
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MARJ3 TEAM
Fully Funded
Fully Funded
Fully Funded
More than year
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