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Material Development Data Scientist

4 months ago

Richland, United States Pacific Northwest National Laboratory Full time

Responsibilities



The Experimental and Computational Engineering Group is seeking a data scientist to join a multidisciplinary team to apply machine learning (ML) principles to accelerate the development and optimization of materials used in advanced manufacturing techniques for nuclear-related purposes.

Apply knowledge of statistics, machine learning, and data modeling to integrate and clean data, recognize patterns, address uncertainty, pose questions, and make discoveries from structured and/or unstructured data Apply ML principles to property, process parameter, and microstructure of novel high entropy alloy compositions developed and fabricated through hybrid manufacturing processes Apply ML principles to accelerate the development and optimization of process parameters and distribution of nano composites within a multicomponent alloy with specific reference to increased irradiation tolerance Develop a ML framework for thin-walled tube forming process for extreme environment applications from current literature for iron-based alloys Participate on interdisciplinary teams to develop innovative solutions for diverse industry and government clients Contribute to technical products, such as journal articles and technical reports, and present at conferences and technical forums
Qualifications

Minimum Qualifications:

BS/BA and 2 years of relevant experience -OR- MS/MA -OR- PhD

Preferred Qualifications:

Demonstrated experience in Python3, R programming language, and PowerBI Demonstrated experience working with alloy compositions, including multicomponent alloys and novel high entropy alloys Demonstrated knowledge of hybrid manufacturing processes Understanding of irradiation impacts to alloy parameters
Hazardous Working Conditions/Environment

Not applicable. 


Additional Information

Not applicable. 


Testing Designated Position

This is not a Testing Designated Position (TDP).