Resilence in Edge Computing Learning Systems

Research Fields: Resilence in ML Systems; Distributed Decision Making.

Description: (contact: Dr Christos (Chris) Anagnostopoulos)

Enrolment & Opportunity: The successful candidate will enrol as a PhD student at the School of Computing Science, University of Glasgow, under the supervision of Dr Christos Anagnostopoulos will join the Data Science & Distributed Computing (Essence) Lab, University of Glasgow. Our lab explores several different issues such as: distributed ML, statistical learning, scalable & adaptive information processing, and data processing algorithms.

Skills: The ideal candidate will have a background in Computer Science and background in either Mathematics and/or Statistics. Special areas of interest include: mathematical modelling/optimization. A good understanding of the basic Machine Learning and Adaptation algorithms as well as an MSc in one of the above areas will be a considerable plus. Programming skills (Python/Matlab/Java), good command of English and team work capacity are required.

Distributed Learning Systems

Research Fields: Distributed ML; Federated/Local Learning at the Edge.

Description: (contact: Dr Christos (Chris) Anagnostopoulos)

Enrolment & Opportunity: The successful candidate will enrol as a PhD student at the School of Computing Science, University of Glasgow, under the supervision of Dr Christos Anagnostopoulos will join the Data Science & Distributed Computing (Essence) Lab, University of Glasgow. Our lab explores several different issues such as: distributed ML, statistical learning, scalable & adaptive information processing, and data processing algorithms.

Skills: The ideal candidate will have a background in Computer Science and background in either Mathematics and/or Statistics. Special areas of interest include: mathematical modelling/optimization. A good understanding of the basic Machine Learning and Adaptation algorithms as well as an MSc in one of the above areas will be a considerable plus. Programming skills (Python/Matlab/Java), good command of English and team work capacity are required.

Model Reusability at the Edge

Research Fields: Model re-usability at the Edge; Multi-task Learning at the Edge.

Description: (contact: Dr Christos (Chris) Anagnostopoulos)

Enrolment & Opportunity: The successful candidate will enrol as a PhD student at the School of Computing Science, University of Glasgow, under the supervision of Dr Christos Anagnostopoulos will join the Data Science & Distributed Computing (Essence) Lab, University of Glasgow. Our lab explores several different issues such as: distributed ML, statistical learning, scalable & adaptive information processing, and data processing algorithms.

Skills: The ideal candidate will have a background in Computer Science and background in either Mathematics and/or Statistics. Special areas of interest include: mathematical modelling/optimization. A good understanding of the basic Machine Learning and Adaptation algorithms as well as an MSc in one of the above areas will be a considerable plus. Programming skills (Python/Matlab/Java), good command of English and team work capacity are required.