Postdoctoral Position Available At Argonne National Laboratory On Machine Learning Workflows to Develop Molecular Dynamics Force-Fields

The Theory and Modeling group at the Center for Nanoscale Materials, Argonne National Laboratory, has immediate postdoctoral openings in the area of computational modeling, machine learning and data analysis of materials. Specifically, the research involves development of machine learning workflows and tools to bridge the electronic, atomistic and mesoscopic (coarse-grained) scales. The postdoctoral researcher will have the opportunity for extensive collaborations with industrial collaborators as well as various experimental (APS, CSE, and MSD) and computational groups at NST and MCS divisions at Argonne.

The applicants should have strong programming skills and expertise in at least two or more of the following fields:

• Molecular dynamics (preferably atomistic and coarse-grained MD) of solid-liquid interfaces and microstructure evolution in inorganic systems and/or polymers/colloids
• Numerical methods and optimization (e.g. machine learning including deep neural networks, data mining, genetic algorithms, clustering techniques etc.)
• Data analysis and/or scientific visualization (e.g. feature detection and tracking of highlevel structures, classification, statistical summaries, comparisons between models and experiments)
• Experience in software development and workflows is highly desirable
• Experience with atomistic or first principles simulation (DFT and ab-initio molecular dynamics simulations) of a wide variety of materials systems,
• Experience in developing empirical force fields for classical molecular dynamics of surfaces and interfaces will be considered an advantage

The postdoctoral researchers will work in a dynamic team of staff scientists at Argonne National Laboratory. Within the team we have extensive experience with molecular dynamics simulations, reactive empirical force fields, chemical dynamics, machine learning and numerical algorithms, data analysis, experimental characterization and imaging. Our research has involved methodology and algorithm development in conjunction with extensive applications in the fields of nanoscience and energy-related materials. The project will also involve significant interactions with industry and is cross-divisional collaboration between the NST, CSE, MSD and MCS divisions at Argonne. The successful candidate will be offered a competitive package, commensurate with qualifications and experience. Initial appointment will be for a period of one year and will be renewable for two additional years. A PhD in theoretical physics/ chemistry, computational materials science, chemical engineering, applied mathematics or a related field is required. Applicants must have received their PhD within the last 5 years. Review of applications will begin immediately and continue until the position is filled. Interested candidates should send their CV and names of references to Dr. Subramanian Sankaranarayanan ([email protected]).