Postdoctoral Researcher – AI Development for Materials Design

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As a flagship research center in nanoscience and nanotechnology, our mission is to open and explore new frontiers of knowledge at the nanoscale, and bring value to society in the form of new understanding, capabilities and innovation, while inspiring and providing broad training to the next generations of researchers. Our values are Commitment, Collaboration and Transformation.

Our research lines focus on the newly-discovered physical and chemical properties that arise from the behaviour of matter at the nanoscale. ICN2 has been awarded with the Severo Ochoa Center of Excellence distinction for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different areas of nanoscience and nanotechnology.

Job title: Postdoctoral Researcher - AI Development for Materials Design

Research area or group: Theoretical and Computational Nanoscience Group

Description of Group/Project: We are building an optimisation-driven framework that makes AI models reliably operate advanced scientific software (e.g., DFT, Wannierisation, and quantum-transport codes) and (ii) uses heuristic optimisation to explore and improve materials candidates-especially 2D/vdW structures-for target electronic/spintronic properties.

The postdoctoral researcher will lead the development of databases build using molecular dynamics, the MACE foundation models and density functional theory.

Main Tasks and responsibilities:

AI4LSQUANT aims to accelerate quantum modelling by learning fast, accurate surrogates of electronic Hamiltonians. The postdoctoral researcher will develop graph neural networks based on the MACE architecture to predict Hamiltonian elements for 2D materials and van der Waals heterostructures, with a focus on spin-orbit coupling and symmetry consistency. The models will interface with existing DFT and quantum-transport workflows to validate band structures and derived properties.

Main Tasks and Responsibilities:

Model design and training: Adapt and extend MACE-style equivariant GNNs for Hamiltonian prediction (including spin and SOC), enforcing physical constraints such as Hermiticity, sparsity, and symmetry.
Data pipeline: Curate datasets from DFT calculations (and, where relevant, Wannier/TB extractions); implement preprocessing, splits, and rigorous validation.
Metrics and validation: Define and track metrics (MAE on Hamiltonian elements, band-structure error, DOS overlap, transport-relevant figures); compare against classical parameterisations.
Uncertainty and active learning: Integrate uncertainty estimation (ensembles or evidential methods) to prioritise new calculations and improve data efficiency.
Integration: Export learned Hamiltonians to downstream simulation tools for band/transport checks; maintain reproducible pipelines (configs, seeds, provenance).
Collaboration and reporting: Work with the PI and team, contribute clean, well-tested Python code, document results, and prepare internal reports and manuscripts.

Requirements:

Minimum (required)

PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related.
Solid knowledge molecular dynamics.
Practical experience in working in R&D projects with companies.
Strong Python stack; good software practices (git, testing).
Comfortable with Linux/HPC environments.

Preferred (nice to have)

Experience with equivariant GNNs (e.g., E(3)-equivariance), MACE or related message-passing models.
Familiarity with force fields methods.

Summary of conditions:

Full time work (37,5h/week)
Contract Length: 6 months
Location: Bellaterra (Barcelona)
Salary will depend on qualifications and demonstrated experience.
Support to the relocation issues.
Life Insurance.
Work-Life Balance and Flexibility with flexible work schedules
28 holidays per year
Flexible compensation plan: tax advantages contracting some products (health insurance, childcare, training, among others.)
Training activities: languages, mentoring programme, wellbeing programme.
International environment

Estimated Incorporation date: December 2025/January 2026

How to apply:

All applications must be made via the ICN2 website and include the following:

A cover letter.
A full CV including contact details.
2 Reference letters or referee contacts.

Deadline for applications: 10/12/2025

Funded by PCI2023-143399 MICIU/AEI/10.13039/501100011033 and co-funded by the European Union and the European Research Council AI4SPIN (GA#101078370)

Equal opportunities:

At ICN2 we foster an inclusive and safe work environment, free from any form of discrimination-whether based on gender, sexual orientation, gender identity, age, origin, culture, religion, disability, or any other personal or social condition. We are committed to ensuring equal treatment and opportunities in all our processes, especially in recruitment, which is based solely on talent, experience, and ability. We implement proactive policies for inclusion and harassment prevention that reinforce our commitment to respect and fairness. If you share these values and are looking to grow in an open and diverse environment, ICN2 is ready to welcome you.

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