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Postdoctoral Fellow in Data-Intensive Modeling of Architected Polymer Blends at Johns Hopkins University

vicky.nguyen's picture

The Nguyen Lab and Elbert Lab invite applications for a postdoctoral position in data-intensive modeling and analysis of architected polymer blends, starting as soon as possible. The position is part of a funded NSF-DMREF grant to create Materials Architected by Adaptive Processing in accord with Materials Genome Initiative (MGI) goals. The candidate will work with Professor’s Nguyen and Elbert on polymer mechanics and development of advanced methods to integrate data-driven materials design and event-driven microservices that integrate experimental characterization, physical modeling, and machine learning with in situ process monitoring and control.

In this unique position, the candidate will develop a research plan that integrates experiments, physics-based modeling, and the development of advanced data science methods.  Experimental work will focus on  characterization of the crystalline and domain structure and their deformation mechanisms of architected polymer blends, These will be used to create physics-based micromechanical models to understand the microstructural origins of the strength and toughness of the blends. Data layer work will emphasize object-oriented Python to capture processing and analysis in a graphical data model and use of stream-processing applications to deploy ML models and realtime connection of materials by design components.  Data-models will link investigator workflows and create rich metadata descriptions allowing reuse and automation of processes across the project.  The postdoc will lead collaborative development of realtime deployment of models in high value portions of the design loop.  

Desired qualifications: PhD in mechanical engineering, materials science, or related fields and experience with large scale numerical simulations of physical systems and data-driven techniques for data analysis. Scientific programming experience with Python and experience with any object-oriented language, knowledge and experience with machine learning, and a willingness to learn experimental methods are a plus. 

Interested applicants should email Dr. Thao (Vicky) Nguyen (vicky.nguyen@jhu.edu) and Dr. David Elbert (elbert@jhu.edu) with a subject line “Postdoc position in Data-Intensive Modeling” and include a (i) Curriculum Vitae with a complete publication list, (ii) contact information of at least three references, and (iii) two representative publications.  Evaluation of candidates will begin immediately and continue until the positions are filled. Initial appointments will be for 12 months with the option to renew.

Johns Hopkins University is an equal-opportunity employer. Women and underrepresented minorities are especially encouraged to apply.

 

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vicky.nguyen's picture

Interested applicants should email Dr. Thao (Vicky) Nguyen (vicky.nguyen@jhu.edu) and Dr. David Elbert (elbert@jhu.edu) with a subject line “Postdoc position in Data-Intensive Modeling” and include a (i) Curriculum Vitae with a complete publication list, (ii) contact information of at least three references, and (iii) two representative publications.  Evaluation of candidates will begin immediately and continue until the positions are filled. Initial appointments will be for 12 months with the option to renew.

 

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