Deep Neuroevolution for Multi-task Learning

Dr G DiFatta
Prof X Hong
Applications accepted all year round
Self-Funded PhD Students Only

Department of Computer Science, University of Reading

About This PhD Project

Project Description
Funding Notes
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Project Description

There is an opportunity to apply for a PhD student position in Machine Learning . The overarching aim of this project is to contribute to theory and applications of machine learning with effective deep Neuroevolution algorithms and optimization methods. Building on established theories and the availability of big data frameworks, you will contribute towards improving the state-of-the-art of the multi-task learning research field. The candidate will design, develop and employ a variety of machine learning algorithms and techniques, including deep learning on big data repositories and complex computational models. The hired candidate will be developing machine learning methods to tackle a set of different multi-task learning problems. The candidate will be guided by one or two supervisor(s) with broad competence machine learning.

Funding Notes

Other subject areas include: Data Analysis, Machine Learning, Artificial intelligence, Deep Learning, Evolutionary algorithms, Data Science, Big Data, Neural Networks, Biologically inspired algorithms.

Related Subjects

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Deep Neuroevolution for Multi-task Learning

University of Reading

Department of Computer Science