The postdoctoral researcher will contribute to the research project, focusing on the development of an automated deep learning framework for the efficient deployment of sliced Open Radio Access Network architectures in 6G networks. Responsibilities include conducting original research, generating and managing datasets, developing and validating deep learning models, automating machine learning processes, and collaborating with a multidisciplinary team. The researcher will also document findings, publish research results, and mentor students involved in the project.
Minimum Qualification
Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on machine learning or network engineering. o Proven experience in developing and deploying deep learning models. o Familiarity with telecommunications, specifically Open RAN architecture and network slicing. o Proficiency in programming languages such as Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch). o Strong analytical and problem-solving abilities. o Excellent written and verbal communication skills in English.
Preferred Qualification
Experience with MLOps principles and automation tools. o A record of publications in peer-reviewed journals or conferences related to machine learning or telecommunications. o Familiarity with data management and monitoring techniques. o Ability to work independently as well as collaboratively in a team environment. o A record of publications in peer-reviewed journals or conferences related to machine learning or telecommunications
Close Date Kindly apply before the closing date.
31/01/2026
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