Deadline:
As soon as possible
Location(s)
France Online
Hybrid
Overview
Details
We are a B2B technology innovation leader pioneering networks that sense, think and act™. At Nokia, we create technology that helps the world act together. We put the world’s people, machines and devices in sync to create a more sustainable, productive and accessible future.
Your career here will have a positive impact on people’s lives and will help us build the capabilities needed for a more productive, sustainable, and inclusive world.
For the past 100 years, Bell Labs has been harnessing the extraordinary imaginations of our researchers to fuel visionary breakthroughs. Our pioneering progress has expanded possibilities to solve humanity’s most pressing challenges. As Nokia's industrial research lab, we keep innovating with purpose, pursuing responsible, sustainable technologies that will have a demonstrative impact on society.
Nokia Bell Labs is the world-renowned research arm of Nokia, having invented many of the foundational technologies that underpin information and communications networks and all digital devices and systems. This research has produced nine Nobel Prizes, five Turing Awards and numerous other awards.
HOW YOU WILL CONTRIBUTE AND WHAT YOU WILL LEARN
Study the potential of Large Language Models (LLMs) in the simulation world, specifically focusing on SUMO (Simulation of Urban Mobility). This internship will provide you with hands-on experience in applying LLMs to enhance simulation-based traffic modelling, scenario generation, and decision-making processes within SUMO.
The internship is a golden opportunity to touch different challenges related to multi-agent LLMs and the road traffic simulation world
Key Responsibilities:
- Investigate the integration of LLMs with SUMO: propose an architecture to interact with SUMO as a Service agent.
- Develop and test methodologies for scenario generation and traffic control using AI-driven models.
- Analyze the simulation results.
- Collaborate with our research and development team to explore innovative applications.
Opportunity is About
Eligibility
Candidates should be from:
Description of Ideal Candidate
Your Skills and Experience
- Currently pursuing/completed a degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Experience with Python and familiarity with SUMO simulation software.
- Knowledge of Large Language Models and their applications.
- Strong analytical and problem-solving skills.
- Ability to work independently and as part of a team.
The internship will take place in Nokia Bell Labs France: Bell-Labs SOLUTIONS/Entreprise Infrastructure & Platform Department, leading the Cooperative Intelligent Transport System.
The premises are located in Massy Palaiseau which is 20 km south from Paris (direct connexion using RER B).
Dates
Deadline: As soon as possible
Cost/funding for participants
ABOUT US
Come create the technology that helps the world act together
Nokia is committed to innovation and technology leadership across mobile, fixed and cloud networks. Your career here will have a positive impact on people’s lives and will help us build the capabilities needed for a more productive, sustainable, and inclusive world.
We challenge ourselves to create an inclusive way of working where we are open to new ideas, empowered to take risks and fearless to bring our authentic selves to work
What we offer
Nokia offers continuous learning opportunities, well-being programs to support you mentally and physically, opportunities to join and get supported by employee resource groups, mentoring programs and highly diverse teams with an inclusive culture where people thrive and are empowered.
Nokia is committed to inclusion and is an equal opportunity employer
Nokia has received the following recognitions for its commitment to inclusion & equality:
- One of the World’s Most Ethical Companies by Ethisphere
- Gender-Equality Index by Bloomberg
- Workplace Pride Global Benchmark
Un-save Opportunity
Internships, scholarships, student conferences and competitions.
