A Doctoral Researcher (PhD student) in Machine Learning for Electron–Phonon Interactions and Wannier-Based Hamiltonians
The ELPH-ML project, led by Dr. Ransell D'Souza at the Department of Chemistry and Materials Science, Aalto University, and the Data-driven Atomistic Simulation (DAS) group, led by Prof. Miguel Caro at the Department of Chemistry and Materials Science, Aalto University, are jointly hiring a Doctoral Researcher. In this position, you will work on a project funded by the Research Council of Finland to build a machine learning framework linking electron–phonon interactions, Wannier-based…
Hamiltonians, and phonon properties for functional materials.
Your role and goals
You will develop data-driven and machine learning workflows to predict Wannier Hamiltonians, phonon properties, and electron–phonon coupling in layered transition-metal dichalcogenides (TMDCs) such as MoS₂, WS₂, MoSe₂, WSe₂, and WTe₂. For training the machine learning models, you will generate datasets from electronic structure theory calculations using Quantum ESPRESSO, Wannier90, and EPW.
Your experience and ambitions
We welcome candidates with a Master's degree in (computational) chemistry, physics, or materials science who are curious about applied machine learning in the natural sciences.
To succeed in this role, you should have:
- A Master’s degree (or equivalent*) in Chemistry, Physics, Materials Science, Mathematics, Computer Science, or a related field.
- Prior programming experience, especially with Python.
- A strong interest in atomistic simulations, machine learning and scientific method and software development.
- Proficiency in English (written and spoken).
What we offer
The fixed term contract is initially for 2 years. The starting salary for Doctoral Researchers is 3142,65€ / month (gross). The position will be filled as soon as a suitable candidate is identified. The starting date for the position is in the autumn 2026.
