Postdoctoral positions in scientific data mining and computational materials design

The group of Professor Gerbrand Ceder at the Department of Materials Science and Engineering at University of California, Berkeley and Lawrence Berkeley National Laboratory has postdoctoral positions available.

The Ceder group is involved in the design of materials, from
ab initio computation to experimental synthesis and characterization. Applications include energy capture, conversion and storage. Our experimental efforts in the synthesis and characterization of novel materials work closely with our theory and modeling group, leading to many opportunities for cross-fertilization. More information about our research group can be found at http://ceder.mit.edu. We particularly value innovation and a passion to bridge fundamental scientific inquiry and high-impact applications. Our group offers candidates the opportunity to work in a highly interdisciplinary and dynamic environment. There are no citizenship restrictions. Starting dates are negotiable. We ask those interested to send their curriculum vitae and references to [email protected].

Positions are available in the following areas:

1. Scientific data mining for materials science applications

This project will involve generating and handling big data, such as the Materials Project database (
http://www.materialsproject.com). The successful candidate will employ and extend existing data mining and machine learning tools to identify materials with desired properties.

The position requires:

• Excellent scientific development skills, preferably in the Python programming language,
• Good understanding of thermodynamics and phase diagrams, and
• Some experience in machine learning and data-mining techniques.

Experience in atomistic simulations, preferably based on density-functional theory, is a plus.

2. Computational design of materials

The successful candidate will work in close collaboration with experimental colleagues by predicting novel materials, providing synthesis guidelines, and/or understanding experimental observations.

The position requires:

• A strong background in solid state physics,
• Excellent practical knowledge of density-functional theory, and
• Good knowledge of thermodynamics and statistical mechanics.

Scientific programming skills are a plus.