Brunel University London is offering a prestigious Research Assistant (MSCA) position with a PhD full scholarship in Networked Scalable Learning. This opportunity is part of the EU HORIZON MSCA DN project ANT: Embedded AI Systems and Applications, which funds 18 PhD scholarships with a total budget of €4.9 million. Selected candidates will engage in groundbreaking research in network protocols, resource optimization, and scalable AI-driven learning models.

Ranked among the best in the UK and globally in computer science, Brunel University provides an exceptional academic environment. This scholarship offers full tuition coverage, competitive salaries, research funding, and collaborative opportunities with renowned researchers, making it an outstanding opportunity for aspiring scholars.

Objectives:

• Develop networked scalable learning techniques for handling increasing data, devices, and network complexity.
• Design network protocols for efficient resource sharing in scalable learning environments.
• Create optimization schemes for resource allocation and dynamic workload distribution.

Expected Results:

• Scalable learning techniques that adapt to dynamic topology, computing loads, and resource availability
• Network protocols to enhance networked scalable learning.
• Optimization strategies for efficient resource allocation and workload distribution

Key Details and Dates

• Application Deadline: 28 March 2025
• Position: MSCA Research
• Assistant: Position no: 16044
• Funding Type: Fully funded
• Host Institution: Brunel University London
• Eligible Countries: All countries
• Eligible Gender: Male/Female
• Target Group: Aspiring PhD students in computer science, AI, machine learning, and related fields
• Fields: Computer Science, Machine Learning, Networked Scalable Learning, Telecommunications, Applied Mathematics
• Study Level: PhD
• Degree Required: Bachelor’s or Master’s in Computer Science, Electrical Engineering, Telecommunications, Applied Mathematics, or related fields
• Number of Opportunities: 1 position
• Duration: 3 years
• Program Language: English
• Host Country: United Kingdom

Benefits and Financial Aids

The scholarship benefits are as follows:

• Full waiver of PhD international tuition fees
• Annual salary of £40,508
• Research training and network fees up to £50,139.84 for three years
• Family allowance (subject to eligibility)
• Generous annual leave and university closure days
• Access to excellent training, development programs, and pension schemes
• Hybrid working approach with a range of health-related support
• Collaborative secondments with ST and IMEC research institutions

Eligibility Criteria

The Research Assistant must meet the following requirements:

• Applicants must hold a Bachelor’s or Master’s degree in Computer Science, Machine Learning, Electrical Engineering, Telecommunications, Applied Mathematics, or related fields
• Proficiency in at least one or two of the following areas: Machine Learning, Large Language Models, Large AI Models, Signal Processing, Wireless Communications, Applied Optimization
• Strong analytical and research skills
• Ability to work independently and collaboratively in a research environment
• Open to international students (self-funded applicants only)

Duties and Responsibilities

The research assistant is responsible for the following activities:

• Lead and execute research projects to meet deliverables and university research strategy.
• Document research activities, analyze data, and prepare reports/papers.
• Build a strong research profile through publications, presentations, and collaborations.
• Support project strategy development and implementation.
• Present findings at conferences, seminars, and workshops
• Assist in securing funding through proposals and grant applications.
• Develop and maintain collaborations with academic, industry, and government partners.
• Support and mentor junior researchers and students.
• Handle administrative tasks related to the research project.
• Contribute to teaching and supervisory activities where applicable.
• Stay updated on advancements in the field and engage in professional development.
• Support the Principal Investigator on other projects as needed.

How to Apply?

To apply for this position, applicants can click on the link below.

Apply Now

• For any queries, email Professor Kezhi Wang at Kezhi.Wang@brunel.ac.uk
• Technical issues? Contact hrsystems@brunel.ac.uk

Further details and information are available on the official website of Brunel University London.

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