HPC Data Scientist - Application-Oriented and Operational Data

Stellenbeschreibung:

Overview

Forschungszentrum Jülich, Jülich, Germany

Full-time
Hybrid
No Salary Information Available

At the forefront of computational research, the Jülich Supercomputing Centre boasts one of Europe’s leading supercomputing facilities, including JUPITER, Europe’s first exascale system. The center continuously optimizes applications for scientific research across the continent. By joining the 'Application Optimization and User Service Tools' lab, candidates contribute to pioneering tasks that support users in maximizing HPC system capabilities. The position aligns with the Collective Agreement for the Public Service (TVöD-Bund), offering competitive salary and social security benefits, and fosters a diverse, inclusive, and equal-opportunity environment.

Responsibilities

Analyze monitoring, application-focused, and operational data utilizing data science expertise.
Introduce new analytical perspectives through advanced statistical methods.
Organize and interpret complex data from various sources, generating clear results visualizations.
Work closely with project partners, collaborating with system software and application developers.
Extend and analyze system benchmarks using synthetic benchmarks and application codes.
Identify optimization opportunities, focusing on architecture-specific scaling and performance strategies.
Provide HPC support and respond to user queries.
Present findings at collaboration meetings, workshops, and conferences.

Benefits

Work on significant issues impacting society within one of Europe’s largest research centers.
Access to comprehensive training and personal/professional development opportunities.
Robust company health management programs.
Family-friendly policies and ideal conditions for work-life balance.
Flexible working hours with the possibility of remote work.
30 days of annual leave plus additional days off between holidays.
Opportunity for extended employment beyond an initial fixed term of 2 years.

Requirements

Master's degree in technomathematics, computer science, engineering, physics, mathematics, or related field.
Proficiency in advanced statistical methods for large data set analysis.
Experience with HPC systems, parallel/distributed computing, and diverse architectures.
Proficient in Unix-based operating systems.
Programming skills in languages such as SQL, Git, Python, Perl, JavaScript, HTML+CSS.
Excellent English communication skills.
Ability to collaborate in a multidisciplinary team environment.