Postdoc position in materials modelling, machine learning and AI to design the next generation materials

Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living. Empa is a research institution of the ETH Domain.

The Laboratory for High Performance Ceramics (HPC) is working on developing new sustainable materials for a range of different application areas including advanced processing, energy generation and storage solutions. We have a range of different production processes and characterization techniques where we are expert. Our group is working on a range of ceramic materials, polymers, as well as the associated sintering and joining processes. We are looking for a machine learning expert combined with a chemistry or materials science background, to allow us to optimize materials properties.

Postdoc position in materials modelling, machine learning and AI to design the next generation materials

Your tasks

• Develop multi-material models at the atomic and molecular level to enable us to optimize materials processes and designs
• Using experimentally obtained data you will optimize the next generation of materials through experimental design including but not limited to 3D printing of polymers, sintering of ceramics, joining of advanced ceramics
• You will be expected to perform processing experiments and to measure and investigate key mechanical and microstructural properties
• Present your results in scientific publications and at international conferences
• Supervision of BSc and MSc students

Your profile

• We are looking for a highly creative self-motivated team player
• You have a PhD degree in Materials Science or Chemistry combined with Machine Learning
• In depth experience of Python, VASP, PySCF, classical mechanics, scientific IT and data handling
• Experience in neural network architectures, bayesian optimization, random forest, kernel models, or gaussian process regression
• Worked with libraries such as pandas, github, tensorflow, pytorch, matplotlib and scikitlearn
• A proven track record in publishing peer reviewed articles
• Fluent in oral and written English

Our offer
The opportunity to do research with our highly motivated and diverse team. You will have the chance to contribute in different projects working in close collaboration with industrial partners to bring your research to fruition and lead developments in the field of machine learning and materials modelling. You will be working at Empa in Dübendorf (near Zürich). The position is available from January 2025 or upon mutual agreement. Initial contract duration is for 18 months.

We live a culture of inclusion and respect. We welcome all people who are interested in innovative, sustainable and meaningful activities - that's what counts.

We look forward to receiving your complete online application including a letter of motivation, CV, certificates, diplomas and contact details of two reference persons. Please submit these exclusively via our job portal. Applications by e-mail and by post will not be considered.