ApplyBlast uses AI to match you with the right jobs, tailor your resume and cover letter, and apply automatically so you can land your dream job faster.
© All Rights Reserved. ApplyBlast.com
ApplyBlast uses AI to match you with the right jobs, tailor your resume and cover letter, and apply automatically so you can land your dream job faster.
© All Rights Reserved. ApplyBlast.com
Ericsson
This thesis opportunity focuses on training and evaluating neural network models for coverage prediction within Ericsson's radio access network. The role involves comparing the performance, memory usage, and CPU efficiency of neural networks against decision tree models using real-world measurement data. The project concludes with a presentation of results to the Ericsson development team.
Ericsson is a Swedish multinational telecommunications company that designs, builds and operates mobile and fixed broadband networks and sells related equipment and services to carriers and enterprises. Its offerings span radio access networks (RAN), 5G core and transport, cloud‑native software, OSS/BSS, managed services, private networks, and IoT solutions, with a strong emphasis on 5G deployment and network automation. Ericsson combines hardware, software and professional services to support large‑scale network rollouts, optimization and operation worldwide. It is a major contributor to telecom standards and R&D, widely chosen for its global scale, patent portfolio and carrier expertise.
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
View leadership team, funding history,
and employee contacts for Ericsson.
Ericsson didn’t post a salary, so this is our estimate from similar listings.
30% below the average for this role
2026 Summer Intern, Machine Learning Engineer, Trajectory Generation (PhD)
General Motors
Master Thesis AI-Based Keypoint Refinement for Autonomous Driving
Bosch
Master Thesis - Optimizing Sparse 3D Occupancy Prediction for Embedded Devices - REF5666W
Aumovio
Masterarbeit: KI-basierte Regelung der Leistungselektronik (w/m/div.)
Bosch Group
Master's Thesis: Computer Vision for Manual Assembly Activity Identification
Volvo Group
Master Thesis AI-based Sensorless Edrive Control
Bosch Group