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Epigenetic evolution of Neural Networks [CDT-AIMLAC Studentship]


Cardiff School of Computer Science & Informatics

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Dr L Turner , Prof Roger Whitaker No more applications being accepted Competition Funded PhD Project (Students Worldwide)

About the Project

In evolutionary learning of neural networks, survival of the fittest is an overarching mechanism to drive progressive performance. This results in the majority of models being discarded in pursuit of optimising against specific objectives. When a trained model is then used as the basis for unseen problems, a new neuroevolutionary process starts without a means of drawing on the efficacy of previously discarded solutions that may be useful. This project will examine whether the characteristics of epigenetic processes [1] found in nature (e.g., biomarkers and gene expression) can inspire methods for preserving phenotype to objective history and how drawing on this can affect learning of new tasks as well as revisiting tasks.

 https://www.youtube.com/watch?v=_aAhcNjmvhc

 [1] Stanley, K. O., D'Ambrosio, D. B., & Gauci, J. (2009). A hypercube-based encoding for evolving large-scale neural networks. Artificial life, 15(2), 185-212.

The UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing (AIMLAC) aims at forming the next generation of AI innovators across a broad range of STEMM disciplines. The CDT provides advanced multi-disciplinary training in an inclusive, caring and open environment that nurture each individual student to achieve their full potential. Applications are encouraged from candidates from a diverse background that can positively contribute to the future of our society.

The project is based at Cardiff University School of Computer Science and Informatics, and the research theme is: T3 - novel mathematical, physical and computer science approaches.

Eligibility 

The scholarships are open to UK/home and international candidates. For more information on eligibility, please visit the UKRI CDT in Artificial Intelligence, Machine Learning & Advanced Computing website

Entry Requirements

A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject. Candidates should be interested in AI and big data challenges, and in the research theme - novel mathematical, physical and computer science approaches.

Applicants whose first language is not English must demonstrate their proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component. (https://www.cardiff.ac.uk/study/international/english-language-requirements)

Applications

Please visit the CDT website http://cdt-aimlac.org/ and follow the instructions.

 Applicants should apply for postgraduate study via the Cardiff University webpage: https://www.cardiff.ac.uk/study/postgraduate/research/programmes/programme/computer-science-and-informatics,

Select the programme Doctor of Philosophy in Computer Science & Informatics with a start date of 1st October 2021, and upload these documents with your application:

• your CV

• a personal statement/covering letter

• two reference letters

• current academic transcripts

In the research proposal section of your application, please specify the project title and supervisors of this project. If you are applying for more than one project, please list the individual titles of the projects in the text box provided. In the funding section, please select ’I will be applying for a scholarship/grant’.

To complete your application please email a pdf(s) of your application to [Email Address Removed]


Funding Notes

The UK Research and Innovation (UKRI) fully-funded scholarships cover the full cost of tuition fees, a UKRI standard stipend of £15,609 per annum (2021/22 rate) with additional funding for training, research and conference expenses. The scholarships are open to UK/home and international candidates. For general enquiries, please contact Rhian Melita Morris: [Email Address Removed]
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