Master Thesis: Energy-efficient Battery SOC Prediction in Radios Base Stations
Luleåonsite
Posted 3w ago · via Eightfold
About this role
Join our Team About the opportunity Ericsson is a world-leading provider of telecommunications equipment and services, supporting mobile and fixed networks in more than 180 countries. Our global and innovative environment gives students the opportunity to work on challenging research problems with real-world impact. The State of Charge (SOC) is a key parameter in battery operation. Accurate SOC estimation is essential for managing the operating conditions of Radio Base Stations (RBSs) and enabling them to support Smart Grid services. However, estimating the SOC accurately throughout a battery’s lifetime remains challenging. In this thesis, you will investigate energy-efficient AI-based methods for predicting battery SOC and optimising battery operation in RBS power systems.…
What we'd score you on
reqspace match rubricFive dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.
1
Skills match
For this role: go, docker, scikit-learn, pytorch, tensorflow…
2
Level fit
We check your title trajectory against the seniority signal of the role.
3
Domain experience
Your work in the role's domain matters more than your years total. We weight recent and direct experience.
4
Recency
A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.
5
Location fit
This role is based in Luleå. We weight your proximity and willingness to relocate.
Score yourself on this role.
Free · no card · written explanation included
Skills in this role
Pulled from the job description. These are the keywords we'll weight when scoring your fit.
godockerscikit-learnpytorchtensorflowkeras
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