Vacancy at MIT for a postdoctoral associate, Materials Science and Engineering (DMSE), to join a collaborative project between the group of Professor Jeffrey Grossman, Professor Yang Shao-Horn, and Dr. Abhishek Aggarwal. The candidate will work in a team consisting of graduate students, Ph.D.-level scientists, and faculty at the intersection of molecular simulation, machine learning, biomolecules, and catalysis. Responsibilities include developing high throughput simulation workflows for water structures in biomolecules; applying and developing machine learning approaches to understand water structures for catalysis as well as for polymer electrolyte design and polymer simulation. The candidate is also expected to take responsibility for student advising/mentoring; and authoring or coauthoring technical presentations, reports, and manuscripts for peer-reviewed journals and conferences.

Job Requirements

REQUIRED: Ph.D. in materials science, physical chemistry, physics, or related field; demonstrated experience and interest in the development of machine learning methods for materials; experience in the computational simulation of materials; highly effective organizational, analytical, problem-solving, and presentation skills; and ability to work both individually and as part of a team.

PREFERRED: Experience in developing novel machine learning methods; experience in high throughput simulation workflows.

Interested applicants should send a cover letter and a curriculum vitae as a single PDF to Professor Jeffrey Grossman at [email protected] and Professor Yang Shao-Horn at [email protected]. Applicants should also arrange for two confidential reference letters to be sent to the same address.