### 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.