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# Using Linux PSI

- **Company:** NXP Semiconductors
- **Location:** Eindhoven, Netherlands
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Bash Shell, Command-Line Interface, Data Centers, Linux, Distributed Systems, Job Scheduling, Python (Programming Language), Network File Systems, Performance Tuning, Software Engineering, Scripting, High Performance Computing, Information Technology, Performance Monitor, Programming Languages
- **Published:** August 26, 2026
- **Apply:** https://www.careerjet.nl/job/nl50d2dd426985c92dc4ba6a57ee1c5ce3/eaa

## About the Role

* Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, Electrical Engineering, Data Science, or a related field.
 * Basic knowledge of Linux operating systems and command-line tools.
 * Interest in High-Performance Computing (HPC), distributed systems, and infrastructure engineering.
 * Experience with scripting or programming languages such as Python, Bash, or similar.
 * Strong analytical and problem-solving skills with an interest in data analysis.
 * Familiarity with Linux performance monitoring tools is a plus.
 * Self-driven, curious, and comfortable working on research-oriented assignments.
 * Good communication skills and ability to work independently and within a team.

What You'll Learn

 * High-Performance Computing environments and job scheduling concepts.
 * Linux performance monitoring and Pressure Stall Information (PSI).
 * Data analysis and predictive modeling techniques.
 * Datacenter infrastructure, storage systems, and NFS performance optimization.
 * How data-driven insights can be used to improve large-scale engineering workflows.

## Description

* Investigate how Linux PSI metrics can be collected and associated with individual jobs within the IBM LSF scheduling environment.
 * Analyze CPU, memory, and I/O pressure data from EDA workloads.
 * Identify workload patterns and resource requirements using PSI measurements.
 * Explore the relationship between I/O pressure and NFS storage performance.
 * Develop and validate a basic model for predicting job I/O requirements.
 * Provide recommendations on how PSI-based insights can improve scheduling decisions across local and remote datacenter resources.
 * Document findings and present recommendations to the HPC engineering team.


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