PhD Researcher: GPU-Driven Stellar Dynamos & Exoplanets

Aalto University Executive Education Oy; Espoo; Hybrid; EUR 30,000 - 41,000; Full time

Job summary

Aalto University Executive Education Oy invites applications for a Doctoral researcher to join the Department of Computer Science in Espoo. The project focuses on modelling stellar dynamos, ML-assisted analysis, and GPU-accelerated radiative transfer within a multi-team environment.

The successful candidate will work on global and local MHD simulations, collaborate with international partners, and contribute to teaching per department practices.

Qualifications

• Master’s degree completed before the contract starts in astrophysics, physics, computational science, or closely related field.
• Experience with HPC, parallel distributed programming, and GPU programming.
• Background in astrophysical fluid dynamics and/or magnetohydrodynamics.
• Experience with radiative transfer in astrophysics and ML for scientific data.
• Strong programming skills in C/C++/Fortran and Python with reproducible workflows/version control.
• Excellent English communication skills.

Responsibilities

• Develop and implement data-driven dynamo models for host stars.
• Design and run large-scale global solar/stellar dynamo simulations on HPC resources.
• Prepare datasets for ML analysis and model selection with observational constraints.
• Interface with SWMF modules to model stellar coronae and winds.
• Disseminate results in journals and conferences; contribute to open data releases.
• Participate in teaching following department practices.

Skills

Master's degree

Computational physics

HPC & GPU programming

MHD / astrophysical fluid dynamics

Radiative transfer

Machine learning

Programming: C/C++/Fortran, Python

English communication

Education

Master’s degree in astrophysics or related

Tools

SWMF-like models

Job description

Aalto University Executive Education Oy invites applications for a Doctoral researcher to join the Department of Computer Science in Espoo. The project focuses on modelling stellar dynamos, ML-assisted analysis, and GPU-accelerated radiative transfer within a multi-team environment.

The successful candidate will work on global and local MHD simulations, collaborate with international partners, and contribute to teaching per department practices.