"Postdoctoral Fellow in Material Science & Mechanical Engineering"

Postdoctoral Fellow in Material Science & Mechanical Engineering

Company:
Harvard University

Job Location:
Cambridge, Massachusetts

Category:
Physics

Type:
Full-Time

School: Harvard John A. Paulson School of Engineering and Applied Sciences

Department/Area: Material Science & Mechanical Engineering

Position Description

The Materials Intelligence Research group of Prof. Boris Kozinsky at Harvard University is seeking researchers at the postdoc level to develop and apply first principles and machine learning methods for computational materials physics and chemistry.

Projects include:

1. The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned interatomic potential to incorporate materials response. Resulting models are implemented in LAMMPS and are used to perform ML-accelerated large-scale dynamics simulations to investigate the evolution of polarization and magnetization degrees of freedom. Efforts are also aimed at learning computationally lean and geometrically rich representations and designing methods for quantifying uncertainty of predictions. Qualifications: Familiarity with machine learning interatomic potentials, CPU and GPU parallelization, knowledge of LAMMPS and molecular dynamics, experience with first principles calculations of dielectric and magnetic response.
2. Development of machine learning methods for exchange-correlation functionals. Current work in the group is focused on improvements and performance optimizations for the recently developed CIDER formalism for designing non-local XC functionals, with an eye toward applying the resulting functionals to currently intractable problems in catalysis and energy storage materials. Effort is aimed at generating training sets with high-order quantum calculations and designing combined models for the exchange and correlation energy using non-local features of electronic density and orbitals. Qualifications: Experience with developing efficient numerical algorithms and modifying electronic structure DFT or quantum chemistry software (e.g. Quantum Espresso, PySCF, GPAW), fluency with electronic structure theory and quantum chemistry, experience with machine learning regression methods.

Preferred start date as soon as possible but flexible.

Basic Qualifications

PhD in Physics, Chemistry, Materials Science, Computer Science, Applied Mathematics or related fields by the time the appointment begins.

Special Instructions

Applicants should include a full CV, cover letter summarizing your experience, list of reference contacts (minimum of 3), and up to 3 publications.

Contact Information

Prof. Boris Kozinsky

Contact Email: bkoz@g.harvard.edu

Salary Range

$67,600 - $91,826

Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.

Minimum Number of References Required: 3

Maximum Number of References Allowed: 3