Postdoctoral Researcher in Materials Science
1 week ago
Postdoctoral Fellow in Material Science
Job Description:Harvard University's Materials Intelligence Research group, led by Prof. Boris Kozinsky, is seeking a postdoctoral researcher to develop and apply first principles and machine learning methods for computational materials physics and chemistry.
Research Focus:The group is working on developing equivariant neural network models, such as NequIP and Allegro, for interatomic potentials, and Bayesian Force Fields in the FLARE framework. These models aim to advance the state of the art in accuracy and data efficiency, and are implemented in LAMMPS for large-scale dynamics simulations.
Qualifications:- Experience with implementation of machine learning methods and development of high-performance scientific software with CPU and GPU parallelization, knowledge of LAMMPS.
- Computational investigations of catalytic reactions and ionic transport.
- Development of machine learning for exchange-correlation functionals.
- Familiarity with machine learning interatomic potentials, molecular dynamics, experience with modeling complex chemical systems, fluency in chemical kinetics and thermodynamics, understanding of dimensionality reduction and classification methods.
- Experience with developing efficient numerical algorithms and modifying electronic structure DFT or quantum chemistry software.
Applicants should include a full CV, cover letter summarizing their experience, list of reference contacts (minimum of 3), and up to 3 publications.
Equal Opportunity Employer:Harvard University is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status.
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