positions

Task: Networked scalable learning (WP2)

Host institution: BUL

Country: United Kingdom

Supervisor: Prof. K. Wang [BUL]

Co-supervisors: Dr. J. Famaey [IMEC]; Dr. D. Pau [ST]

Objectives: 1) To design networked scalable learning techniques to adapt to the increasing amounts of data, devices and network complexity; 2) To design network protocols to facilitate resource sharing in networked scalable learning; 3) To develop optimisation schemes for resource allocation and dynamic workload distribution.

Expected Results:  1) Networked scalable learning techniques that accommodate the dynamic topology, computing loads, data volume, resource availability and quality of service (QoS) requirements; 2) Network protocols to facilitate networked scalable learning; 3) Optimisation schemes for dynamic resource allocation and computing load distribution.

PhD enrolment: Doctoral School of BUL

Planned secondments: 

• ST (3 months, M16-M18): Networked scalable and continual learning in dynamic evolving environment, with Dr. D. Pau (KPI: joint paper)

• IMEC (4 months, M27-M30): Efficient data transfer protocols for networked scalable learning, with Dr. J. Famaey (KPI: joint paper)

Candidate profile: computer science, machine learning, electrical engineering, telecommunication engineering, applied mathematics or related areas

Desirable skills/interests: machine learning, large language model, large AI model, signal processing, wireless communications, applied optimisation (the applicant should be proficient in at least one or two of the skills)

Application Deadline: February 14, 2025, AoE

Descriptions of all the 18 DC Positions

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