Sd-25163 Researcher in Machine-learning Potentials for Nanohardness Simulations

Description
**Temporary contract | 30 months | Belval**:
**Are you passionate about research? So are we Come and join us**:
The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.

You will be hosted in the Process Modelling, Automation and Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and experimental setups for discovering and optimising chemicals, materials, and related processes.

You will collaborate with the Plasma & Vapour Deposition Processes (PLAVA) group at LIST and with our industry partner, a global leader in the development and manufacturing of hard materials, who will perform nanoindentation experiments and provide in-depth materials expertise.

**How will you contribute?**:
You will model the plastic deformation of solid solutions of tungsten carbide in a cobalt binder under nanoindentation, including MD-based hardness predictions and defect analyses, to gain fundamental insights into this material and support tailoring its properties.

For this, you will:

- Contribute to method development for ultra-fast MLIPs (Xie et al., npj Comput. Mater., 2023)
- Develop realistic MD simulation protocols
- Conduct large-scale MD simulations on supercomputers and HPC clusters
- Analyse simulation results and compare them with experiments

You will demonstrated expertise in developing machine-learning interatomic potentials (MLIPs) for large-scale molecular dynamics (MD) simulations of materials. Together, we will push the boundaries of ultra-fast MLIPs to simulate the nanoindentation of cemented carbides, a material of industrial relevance, in agreement with and beyond experimental nanoindentation results.

**Education**
- PhD in materials science or related discipline

**Experience and skills**
- Experience in developing MLIPs, including good programming skills in Python and C, demonstrated via contributions to code repositories
- Experience with large-scale MD simulations, ideally with LAMMPS, demonstrated via corresponding roles in publications
- Experience with density functional theory (DFT) calculations, ideally with VASP, demonstrated via corresponding roles in publications
- A solid, relevant, and impactful publication record
- A friendly, motivated, positive, hands-on, initiative-taking, collaborative attitude and demeanour

**Language skills**
- Good level both written and spoken English

**Your LIST benefits**:

- An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
- Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
- Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
- An environment encouraging curiosity, innovation and entrepreneurship in all areas
- Personalized learning programme to foster our staff’s soft and technical skills
- Multicultural and international work environment with more than 50 nationalities represented in our workforce
- Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
- Gender-friendly environment with multiple actions to attract, develop and retain women in science
- 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
- Flexible working hours, home working policy and access to lunch vouchers
- A motivation letter specific to the position. The letter should detail your experience and provide factual evidence for it (e.g., specific publications, open-source code repositories).
- A scientific CV. It should include contact details and link to your Google Scholar profile.
- List of publications (and patents, if applicable)
- Contact details of 2 references

**Application procedure and conditions**
- We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes.
- LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability.

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