Research Assistant or Post-doctoral Fellow Grant Title: Energy-efficient resource management in Edge computing using Generative AI for eHealth system We are at the Computer & Network Engineering and the Big Data Analytics Center seeking a highly motivated and skilled Research Assistant (RA) or Post-doctoral Fellow to join our research team. This position is funded by a grant focused on developing innovative solutions for energy-efficient resource management in Edge computing, specifically tailored for eHealth systems through the application of Generative AI. Position Overview This role involves conducting cutting-edge research at the intersection of Edge Computing, Generative AI, and eHealth. The successful candidate will contribute to the design, development, and evaluation of novel algorithms and frameworks aimed at optimizing energy consumption and resource allocation in distributed computing environments for healthcare applications. This includes leveraging Generative AI techniques to predict resource needs, optimizing task scheduling, and enhancing the overall efficiency and reliability of eHealth services. Responsibilities • Conduct in-depth literature reviews and stay updated on the latest advancements in edge computing, generative AI, and eHealth. • Design and implement energy-efficient resource management algorithms and protocols for edge computing environments. • Develop and apply Generative AI models for predicting resource demands, optimizing task offloading, and enhancing system performance in eHealth applications. • Perform simulations, experiments, and real-world deployments to validate proposed solutions. • Analyze and interpret research data and prepare high-quality research publications for top-tier conferences and journals. • Collaborate with team members, including faculty, other RAs, and graduate students. • Assist in grant writing and project reporting as required. • Mentor junior researchers and students (for Post-doctoral Fellow). • Present research findings at national and international conferences.
Minimum Qualification
Master of Science
Preferred Qualification
PhD
Expected Skills
- Master's or PhD degree in Computer Science, Electrical Engineering, or a related field. • Proficiency in programming languages such as Python, Java, or C++. • Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch). • Excellent problem-solving and analytical skills. • Ability to work independently and as part of a team. • A publication record in reputable conferences and journals related to edge computing, AI, machine learning, or eHealth. • Demonstrated expertise in Generative AI techniques (e.g., GANs, VAEs, Transformers) and their applications. • Solid understanding of resource management, task scheduling, and energy efficiency in distributed systems. • Excellent written and verbal communication skills.
Interested candidates should submit the following documents: - Curriculum Vitae (CV)with a list of publications (if any). - Cover letter detailing r
Salary Range
4000 - 10000
Close Date Kindly apply before the closing date.
Open until filled
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