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Master Thesis: AI for Silicon Design at Ericsson

Stockholm, , Sweden -

Full Time

Start Date

Immediate

Expiry Date

29 Jan, 26

Salary

0.0

Posted On

31 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI, Machine Learning, EDA Systems, Silicon Design Methodology, Python, Data Engineering, ML Frameworks, PyTorch, TensorFlow, Data Pipeline, Metadata, Data Governance, Anonymization, Reinforcement Learning, Job Partitioning, Parallelization

Industry

Telecommunications

Description

Develop an intelligent assistant to answer flow-related questions, diagnose job failures, and explain EDA tool behaviors. Integrate NLP and retrieval-augmented generation (RAG) with documentation, logs, and historical data. Enable self-service troubleshooting and contextual design guidance. Currently pursuing a MSc in Computer Science, Electrical Engineering, Data Science, or related field. Strong interest in AI/Machine Learning, EDA systems, or Silicon Design Methodology. Proficiency in Python, data engineering, ML frameworks (PyTorch/TensorFlow), and familiarity with EDA flows are highly valued. Build a scalable data pipeline to collect, curate, and correlate metadata from millions of jobs (runtime, logs, resource usage, success/failure metrics). Ensure secure data governance and anonymization following enterprise policies. Design RL agents to recommend or automatically tune runtime parameters (e.g., job partitioning, parallelization, memory tuning, license affinity). Implement feedback loops for continuous flow-level performance improvement.Ensure secure data governance and anonymization.

Responsibilities

Develop an intelligent assistant to answer flow-related questions and diagnose job failures. Build a scalable data pipeline to collect and curate metadata from millions of jobs.