PhD Student FPI Reference: PID2025-170514OB-I00 - (R1)

Barcelona Supercomputing Center; España; On-site; EUR 29,000 - 38,000; Full time

Benefits offered by this job

Restaurant tickets

Private health insurance

Relocation support

Job summary

BARCELONA SUPERCOMPUTING CENTER in Barcelona seeks a PhD student to join the HPC4ES team within the CES group. The project targets performance, scalability and energy efficiency of Earth system models and workflows, with emphasis on AI-enabled approaches and the Autosubmit workflow manager.

The candidate will develop a PhD thesis combining original research, experimentation on HPC infrastructure, and peer-reviewed publications, collaborating with an international team across supercomputing and

Qualifications

• Master’s degree in a relevant field (completed or in final stage) with access to a PhD program.
• Strong programming skills in Python and/or compiled languages (C/C++, Fortran).
• Familiarity with UNIX/Linux environments, command-line usage, and shell scripting (Bash).
• Basic understanding of HPC environments and job schedulers (e.g., Slurm).
• Knowledge of software engineering practices including Git.
• Fluency in spoken and written English.

Responsibilities

• Conduct original research on HPC performance for end-to-end workflows.
• Publish results in high-impact journals and present at conferences.
• Complete a PhD thesis synthesizing theory, experiments, and software solutions.
• Collaborate on departmental projects and international initiatives.

Skills

Python

C/C++

Fortran

UNIX/Linux

Bash

Git

English

Education

Master’s degree in CS / HPC

Tools

Autosubmit

Cylc

Airflow

Snakemake

Job description

Organisation/Company BARCELONA SUPERCOMPUTING CENTER Research Field Mathematics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 19 Nov 2026 - 00:00 (Europe/Andorra) Country Spain Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Context And Mission

We are seeking a PhD student to join the High Performance Computing for Earth Sciences (HPC4ES) team, within the Computational Earth Sciences (CES) group of the BSC Earth Sciences Department. HPC4ES develops methods and tools to understand and improve the computational performance, scalability and energy efficiency of Earth system models and their workflows. The team works closely with climate scientists, model developers and European supercomputing centres.

The position is funded through an FPI grant associated with UNE DT. The doctoral research will address the digital continuum connecting HPC systems, heterogeneous CPU and GPU resources, storage, data services and analysis infrastructures. Weather and climate simulations depend on a complete workflow, from input preparation and model execution to data transfer, post-processing and delivery of scientific results. Their overall performance depends on how these stages interact, including scheduling delays, data availability and interruptions during execution.

The candidate will investigate methods to predict workflow completion times and resource requirements, and to optimise both individual components and the coordination of computation and data movement. The research will also develop and evaluate AI agents that retain simulation state over weeks or months, monitor progress, diagnose execution problems and carry out verified recovery actions, requesting human intervention when needed. These methods will be assessed using weather and climate workflows, including physical and AI model components, to reduce time to results, resource consumption and manual intervention while preserving scientific validity and reproducibility.

The work will build on the research environment and software developed within CES, including the Autosubmit workflow manager, with applications relevant to Destination Earth, TerraDT and ESiWACE European projects. The candidate will develop a PhD thesis combining original research, experimental evaluation on advanced HPC infrastructure and peer-reviewed publications, while collaborating with an international team working at the intersection of supercomputing, Earth system modelling and artificial intelligence.

Key Duties

• Undertake original research centered on High-Performance Computing (HPC) computational performance, expanding the evaluation scope toward end-to-end scientific workflows and incorporating the computational performance of AI models, particularly within earth science applications.
• Publish research findings in high-impact, peer-reviewed journals and present results at international scientific and HPC conferences.
• Complete a PhD thesis synthesizing the theoretical frameworks, empirical methodologies, and software solutions developed throughout the research line.
• Support departmental projects and collaborate on research group initiatives focused on HPC performance and computational science.

Requirements

• Education
  • Master’s degree in Computer Science, High-Performance Computing, Physics, Applied Mathematics, Earth Science, or a related scientific/engineering discipline (completed or in the final stage, granting access to a PhD program).
• Essential Knowledge and Professional Experience
  • Strong programming skills in Python and/or compiled languages (C/C++, Fortran).
  • Familiarity with UNIX/Linux environments, command-line usage, and shell scripting (Bash).
  • Basic understanding of High-Performance Computing (HPC) environments and job schedulers (e.g., Slurm).
  • Knowledge of software engineering best practices, including version control systems (Git).
  • Fluency in spoken and written English.
• Additional Knowledge and Professional Experience
  • Prior exposure to HPC application performance profiling, benchmarking, or resource allocation dynamics.
  • Familiarity with scientific workflow managers or orchestrators (e.g., Autosubmit, Cylc, Airflow, Snakemake).
  • Knowledge of Earth science applications, climate models, or scientific data formats (NetCDF, GRIB, Zarr).
  • Interest or background in machine learning / LLM tools, AI model performance, or software testing/debugging automation.
• Competences
  • Ability to take initiative and prioritize.
  • Strong analytical ability, critical thinking, and problem-solving skills
  • Capacity to work both independently and collaboratively within an international, interdisciplinary team.
  • Good communication and presentation skills to share research progress and results.
  • Motivation and commitment to complete a PhD thesis within the set timeframe.

Conditions

• The position will be located at BSC within the Earth Sciences Department
• We offer a full-time contract (35h/week), a good working environment, a highly stimulating environment with state-of-the-art infrastructure, flexible working hours, extensive training plan, restaurant tickets, private health insurance, support to the relocation procedures
• Duration: Temporary - 4 years renewable
• Holidays: 22 days of holidays + 6 personal days + 24th and 31st of December per our collective agreement
• Salary: we offer a competitive salary commensurate with the qualifications and experience of the candidate and according to the cost of living in Barcelona