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Postdoctoral Fellow in Machine Learning for Energy Efficient IoT Networks

Mohammed VI Polytechnic University
localisationBenguerir, Marrakech-Safi, Morocco
Décryptage du poste par Postule AI

About the Role

Mohammed VI Polytechnic University (UM6P) seeks a postdoctoral fellow in machine learning for IoT networks. This is a research-focused position at a leading African institution committed to applied research and innovation in sustainable development.

Key Responsibilities

  • Publish research findings in high-impact journals in machine learning and IoT networks
  • Supervise graduate and undergraduate students in research activities
  • Contribute to teaching and training activities as applicable
  • Conduct hands-on research in wireless communications and machine learning applications

Required Qualifications

  • PhD in wireless communication, computer science, or related field (or about to complete)
  • Strong publication record in high-impact conferences and journals
  • Hands-on experience in wireless communications
  • Technical expertise in at least one area: multiple access techniques, interference management, energy efficiency, resource allocation, or security against intrusive devices
  • Strong aptitude for teamwork, problem-solving, and collaborative relationships

About UM6P

UM6P is an internationally oriented institution committed to the highest standards of teaching and research. The university emphasizes applied research, innovation, and transdisciplinary collaboration to address real challenges in Africa. The institution provides state-of-the-art infrastructure and promotes academic liberty through research-driven funding models.

Application Requirements

Submit a single electronic zipped folder containing:

  • 1-page cover letter with main research interests
  • Detailed CV
  • 1-page brief research statement

Shortlisted candidates will be invited for an interview.

Cette description d'emploi a pu être reformatée par Postule pour améliorer sa lisibilité et sa présentation. Le contenu et les informations restent fidèles à l'offre d'emploi originale. .