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.