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Master Thesis: Advanced machine learning for telecom scheduler performance at Ericsson

Stockholm, , Sweden -

Full Time

Start Date

Immediate

Expiry Date

06 Jan, 26

Salary

0.0

Posted On

08 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, Deep Learning, Data Science, Communication, Collaboration, NumPy, Pandas, Scikit-learn, JAX, TensorFlow, PyTorch, Random Access Network, English Communication

Industry

Telecommunications

Description

Very curious about new technology, Quick learner with open mind Is currently enrolled in a quantitative MSc program such as Computer Science, Data Science, Communication, or a related field. Has hands-on experience with Python programming and common ML libraries (NumPy, Pandas, scikit-learn, etc.) Ideally has practical experience with deep learning frameworks (e.g., JAX, TensorFlow, PyTorch) Ideally has experience or strong interests with Random access network Communicates well in English and enjoys working in a collaborative environment.

Responsibilities

The role involves conducting advanced machine learning research to improve telecom scheduler performance. The candidate will work collaboratively in a team environment to explore new technologies.