Position Summary:

Better materials are needed to improve the performance and drive down the cost of many devices important to our energy future, including batteries, solar cells, thermoelectrics, and LED lighting materials. While materials discovery is traditionally driven by experiments, the Materials Project (www.materialsproject.org) has created massive simulation-derived data sets based on density functional theory calculations and executed on supercomputing resources. The properties of over 60,000 materials have been computed and serves a user base of over 12,000 researchers, and several new and technologically useful materials have been discovered through this technique.

Specific Responsibilities:

• This project will build further on the Materials Project database, and create a new avenue for understanding and controlling materials properties by applying data mining techniques to extract structure-property relationships needed for materials design.
• A broad and open-ended array of applications will be targeted for the data mining effort, but a major common theme will be descriptor development for crystalline compounds.
• In addition to data analysis, targeted calculations (often in high-throughput) will be performed to “fill in” missing data, to assess and improve data quality, and to build new data sets for public dissemination.
• The end goal is to develop new data, new data mining techniques, and most importantly new physical theories that help reveal structure-property relationships and point the way to materials breakthroughs.

The position is in the group of Dr. Anubhav Jain at Lawrence Berkeley National Laboratory, Berkeley, CA. For more details, please see: https://lbl.taleo.net/careersection/jobdetail.ftl?job=81036&lang=en