logo1
logo-w
  • Home
  • About
    • People
    • Use Cases
  • Research
    • Vision
    • Research Strands
    • Scientific and Technological Advancements
  • Dissemination
    • Publications
    • Software
    • Presentations
    • Videos
    • Events
  • Opportunities
  • News
    • Newsletters
    • In the Media
  • Contact
Menu
  • Home
  • About
    • People
    • Use Cases
  • Research
    • Vision
    • Research Strands
    • Scientific and Technological Advancements
  • Dissemination
    • Publications
    • Software
    • Presentations
    • Videos
    • Events
  • Opportunities
  • News
    • Newsletters
    • In the Media
  • Contact
Facebook-f Instagram Linkedin-in Twitter Youtube

Opportunities

Network slicing, resource allocation and network programmability for O-RAN URLLC services

  • DisCoNet: Distributed Computer Networking
  • Type: Post-doc
Abstract:

SMARTNESS is a joint research center formed by Unicamp, USP, and UFSCar, among other associate universities. Funded by Ericsson and FAPESP, SMARTNESS aims to conduct cutting-edge research on computer networks and digital application services, focusing on the evolution of networking and services by 2030. We seek candidates for this post-doctoral position with a background in mobile wireless networks and modeling tools to conduct research focusing on networking slicing, radio functional split, resource allocation, network programmability, and radio stack acceleration in Open RAN scenarios. We are interested in solving problems related to ensuring end-to-end latency for Ultra-Reliable Low-Latency Communications (URLLC) services by considering multiple functional splits and segregation of services through network slicing, including routing, queueing, and processing. The selected researcher will be responsible for conducting research using modeling tools, implementing algorithmic and AI/ML solutions, and designing and coordinating the deployment and evaluation in real-world devices such as programmable switches, offload-enable interfaces, and hardware acceleration components. Moreover, the researcher must understand and develop solutions considering mobile networks as the target scenario, i.e., Beyond 5G networks based on Open RAN technologies and standards.

Desired skills:

To succeed in this position, you are expected to have strong motivation, a PhD in computer science, computer engineering, or related fields, excellent skills in common computer programming languages (e.g., Go, C/C++, Python), research experience with mobile networks (preferably Open RAN and 5G/Beyond 5G) and modeling tools, knowledge and/or research experience in machine learning techniques, and experience supervising grad and undergrad student.

Application deadline:

November 15, 2024

Location:

Unicamp, UFSCar and eventually at UFG

Funding:

FAPESP

Starting Date:

Jan/Feb 2025

Advisor:

Fabio Verdi, Christian Rothenberg, Flavio Geraldo

Contact: verdi@ufscar.br, chesteve@dca.fee.unicamp.br, flaviogcr@ufg.br

Monthly FAPESP scholarship:
The selected candidate will receive a FAPESP Postdoctoral Scholarship of R$ 12,000.00 per month and an additional 10% for research expenses. For more details, check out Fapesp’s webpage.

Good References:

- How to apply: Interested candidates should complete the online form by November 15, 2024.
- Selection process: Selection of candidates will be based on their motivation, curriculum vitae with the list of publications, training and experience, and a copy of the University Degree certificate. There will be an interview with the finalists, which will take place via videoconference.

logo1
  • Home
  • About
  • Vision
  • Use Cases
  • Research Strands
  • Scientific and Technological Advancements
  • People
  • Opportunities
  • News
  • Contact
  • Home
  • About
  • Vision
  • Use Cases
  • Research Strands
  • Scientific and Technological Advancements
  • People
  • Opportunities
  • News
  • Contact
Facebook-f Instagram Linkedin-in Twitter Youtube

Partnerships

fapesp-300x83
ERI_vertical_RGB-3-300x263
unicamp-300x300
usp-2
Logomarca_UFSCAR-2-300x219

© 2024 SMARTNESS 2030