Postdoctoral Researcher in Computational Materials Science and Materials Informatics at Purdue University Purdue University in United States

Postdoctoral Researcher opening in computational materials science at Purdue University, in the research group of Prof. Arun Mannodi Kanakkithodi (School of Materials Engineering).

The project focuses on ab initio simulations, density functional theory (DFT), computational materials design, materials informatics, and machine learning for materials research. Specific topics include electronic, optical, and defect properties of semiconductors, defect-tolerant and dopable wide-bandgap materials, and prediction of synthesizability and synthesis routes. The group also works on high-throughput DFT, descriptor-based regression models, crystal graph neural networks, and open computational datasets.

Eligible applicants should hold a PhD in Materials Science and Engineering, Physics, Chemistry, or a related field. Strong experience with VASP, solid-state physics, Unix, LaTeX, Python, and programming is expected. Experience with machine learning algorithms, training machine-learning interatomic potentials, and foundation models is desirable, as is familiarity with large language models and strong scientific communication skills.

This is a postdoctoral position, based on the West Lafayette, Indiana, USA campus. The appointment is for one year and may be renewed depending on funding and performance. The post is restricted to US citizens or permanent residents because of funding restrictions.

How to apply: email a single PDF with a 1-page cover letter, CV (max 4 pages), and names, emails, and phone numbers of at least three references to [email protected]. Applications are reviewed immediately and accepted until the position is filled.