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Master Thesis: AI ML for Anomaly Detection in Baseband System Hardware at Ericsson
Karlskrona, Blekinge County, Sweden -
Full Time

Start Date

Immediate

Expiry Date

21 Jan, 26

Salary

0.0

Posted On

23 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, Machine Learning, AI Methodologies, Time Series Analysis, Python, Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch, Apache Spark, Jupyter, Linux, SQL, Data Visualization, Clustering Techniques

Industry

Telecommunications

Description
Background in data science, machine learning, and AI methodologies. Proficiency in time series analysis and related algorithms. Experience with Python and relevant libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch). Experience with Apache Spark (pyspark), Jupyter, Linux, SQL(PostgreSQL). Familiarity with data visualization techniques and tools, such as Grafana. Basic understanding of clustering techniques and statistical methods. Knowledge of power consumption and temperature measurement data from electronic hardware products is a plus. Ability to work independently and systematically, with a problem-solving mindset.
Responsibilities
The role involves applying AI and machine learning techniques for anomaly detection in baseband system hardware. The candidate will work independently and systematically to solve problems related to data analysis.