SD-25280 EXPERIENCE RESEARCHER IN DATA-DRIVEN MATERIALS SCIENCE

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.

Do you want to know more about LIST? Check our website: www.list.lu

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

Permanent contract | Fulltime/40h | Belvaux Are you passionate about research? So are we! Come and join us

How will you contribute?

We seek an experienced colleague with demonstrated expertise in data-driven methods for materials science. Together, we will transform and accelerate materials research via predictions, simulations, and experiments.

Is Your profile described below? Are you our future colleague? Apply now!

A strong candidate should have:

• a pertinent background in materials science or a related discipline, incl. a PhD and postdoctoral or industry experience
• demonstrated experience with data-driven, machine learning, or artificial intelligence methods in materials science
• a proven track record of obtaining competitive or industrial research funding
• demonstrated experience in managing research projects
• a solid and relevant publication record
• (co)supervised bachelor, master, and PhD students
• good programming skills in Python, ideally demonstrated in open-source projects
• a friendly, motivated, positive, hands-on, initiative-taking, collaborative attitude and demeanour

In addition, an outstanding candidate should have:

• won awards and prizes recognising their scientific contributions
• obtained research funding from national, European, and international competitive programs
• coordinated research consortia
• documented work experience in establishing and leading collaborative research projects with private, public and academic partners
• impactful publications, including publications in leading journals and machine-learning conferences
• supervised bachelor, master, and PhD students, and holds PhD supervision rights at a degree-awarding institution
• excellent programming skills, including C++ and Python, ideally demonstrated in open-source projects

Candidates with a computational profile should have demonstrated experience with ab initio and machine learning-accelerated molecular dynamics simulations.

Candidates with an experimental profile should have demonstrated experience with machine learning-based screening or inverse design, as well as with automated or robotic setups.