The Theory Group at Nanogune (Nanoscience research institute at SanSebastian, Spain) is looking for a software engineer candidate who will work on the development of state-of-the-art Machine Learning (ML) techniques applied to Materials Design. The candidate will be responsible for implementing, evaluating and testing modern quantum and classical ML techniques to predict novel materials for hydrogen storage, alternative ways of hydrogen production for internal combustion engines and fuel cells. Access to a quantum computer will be provided.

Key Responsibilities Include

• Gather training data from materials databases and their generation with active learning.
• Process the data to make it accessible to the ML models.
• Find suitable descriptors to feature the molecular and chemical systems.
• Select and train different ML models/architectures (Quantum and Classical ML).
• Evaluate and compare the performance of the models.
• Write product documentation, demos, and training material.

Required Knowledge/Skills/Abilities

• Minimum 1 year of professional software development experience.
• Bachelors or coursework in Computer Science, Applied Mathematics, Physics, or related fields.
• Fluent in Python and C++.
• Comfortable working in Linux and macOS.
• Experienced in Unit Testing.
• Versed Git user.
• Good spoken and written English.
• Comfortable working in an international team.

We offer an international and competitive environment promoting teamwork in a diverse and inclusive environment. We welcome all applicants regardless of age, disability, gender, nationality, race, religion, or sexual orientation.

The position is expected to start on 01/01/2023 and go on for up to 2 years in the Theory group. https://www.nanogune.eu/en/research/groups/theory.

Candidates should apply by completing the form below and attaching the following documents:

A complete CV, motivation letter, and 2 reference contacts, all grouped in a single PDF file

*Application form: https://www.nanogune.eu/en/nanogune/join-us/open-position/333-software-engineer-machine-learning-materials-design

The deadline for applications is 31/12/2022.