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Purdue University

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

Degree Level

Postdoc

Field of study

Computer Science

Funding

Postdoctoral appointment for one year, renewable depending on funding and successful performance. Funding restrictions apply; the position is only open to US citizens or permanent residents. No stipend amount is stated.

Deadline

Expired

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Country

United States

University

Purdue University

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Keywords

Computer Science
Machine Learning
Chemistry
Electrical Engineering
Materials Science
Mathematics
Density Functional Theory
Silicon Technology
Electronic Properties
Computational Materials
Physics

About this position

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.

Funding details

Postdoctoral appointment for one year, renewable depending on funding and successful performance. Funding restrictions apply; the position is only open to US citizens or permanent residents. No stipend amount is stated.

What's required

Applicants must have a PhD in Materials Science and Engineering, Physics, Chemistry, or a related discipline. Strong expertise is required in density functional theory (VASP), solid-state physics, Unix, LaTeX, Python, and general programming. Experience with machine learning algorithms, training machine-learning interatomic potentials, and using foundation models is preferred, along with familiarity with large language models and strong scientific communication skills. The post is restricted to US citizens or permanent residents because of funding restrictions.

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