PhD Position in Opportunistic Architectures Lab

Opportunistic Architectures Lab

Deadline for receipt of applications: September 29, 2022 23:59 AoE (30 September 2022, 13:59h Europe/Madrid Time)

The IMDEA Networks’ Opportunistic Architectures Lab lead by professors Vincenzo Mancuso and Marco Ajmone Marsan invite applications for multiple PhD positions in the area of design, modeling and performance evaluation of intelligent cellular networks and associated services.

As a member of the team, the PhD student will be involved in cutting-edge research, will participate in the national and international research projects with academic and industrial partners, and will perform analytical and experimental work with other team members and international collaborators.

The position offers:

• Working in a vibrant, collaborative, multi-cultural and
• English-speaking environment
• The expectation to publish at top-tier venues in networking

Skills Required:

• Excellent analytical, technical and problem solving skills
• Very good knowledge of network protocols and architectures, and associated methodologies for data analytics
• Very good organization and communication skills
• High proficiency in programming and English

Academic Qualifications:

• Bsc or Msc in computer science, telecommunication engineering, electrical engineering, or a related field

Experience (optional):

• Experience in developing analytical models and/or tools for statistical analysis of data
• Experience in developing machine learning applications

This contract can be cofounded by project AEON-CPS TSI-063000-2021-38, funded by the European Union-NextGenerationEU and the Ministry of Economic Affairs and Digital Transformation through the Spanish Recovery, Transformation and Resilience Plan under Royal Decree 1040/2021 for the granting of funds to public research centers and foundations and Spanish public universities to carry out innovative projects in the deployment of advanced 5G and 6G technologies.

This contract can be cofounded by project ECID (PID2019-109805RB-I00) funded by the Ministry of Science and Innovation.