Idaho National Laboratory (INL) is seeking highly motivated applicants for the position of Data Science Researcher in the Clean Energy and Transportation Division to provide thought leadership and develop implementable data science strategies, particularly to implement a vison of future prognostics & health management that leverages the future¿s fully effective sensing and information technologies to accelerate clean energy technology development by robust designs that avoid faults or failures in use. The position is a key position within the Energy & Environment Science and Technology (EES&T) Directorate, INL's principal multi-mission organization, focused on research to advance clean energy systems, advanced transportation, advanced process for manufacturing, environmental sustainability related to energy and defense systems.
INL¿s Clean Energy and Transportation Division is making significant efforts to advance data science and analytics to enable and advance the research enterprise in integrating advanced battery systems, electric drives (including alternative fueled vehicles) and charging infrastructure technologies. The Division engages in research activities in testing, data collection and analysis to evaluate and validate performance of advanced energy storage and transportation systems. The complexity of these systems is growing and the volume and variety of data available necessitates disruptive advances built on the triad of advanced information processing and data analytics; machine-based artificial intelligence; and innovative collaboration between humans and human-based intelligence. The successful candidate will be responsible for key inputs to capability roadmaps and leading the maturation of the data science capability to facilitate the development of energy storage systems, advanced vehicles and related supporting infrastructure.
Masters degree in mechanical, electrical, automotive, computer science, data analysis or related plus 5 years work experience in related engineering research or a PhD in mechanical, electrical, automotive, computer science, data analysis or related plus 3 years related engineering research.
–Evidence of successful research and applications experience in Data Science, including but not limited to Artificial Intelligence, Machine Learning, Data Analytics, Natural Language Processing and Human-Machine Interaction
–Extensive awareness of the state of the art of academic research in the technical areas identified above
–Experience defining R&D program objectives and writing proposals, preparing and presenting research plans and results to internal and external senior staff, and implementing and tracking projects in conjunction with research agencies including but not limited to the Department of Energy, National Science Foundation, IARPA, AFRL, ONR, ARL, DARPA, or other US Department of Defense Research and Development entities.
–Experience applying research rigor to the growing field of advanced data analysis, predictive analytics, agent-based modeling and the development of diagnostic and prognostic tools.
–Demonstrable experience performing engineering analysis, developing engineering tools, preparing technical reports and publications, and conducting professional presentations and other scholarly activities.
–The ideal candidate will have experience with data acquisition, computing programming, as well as demonstrable experience in developing activity-based and agent-based models, simulation capabilities, big data collection and management, data fusion and mining, machine learning and cognitive systems and deploying algorithms for developing new insights and approaches to explaining energy or defense systems.
–Domain knowledge of system and subsystem technologies in advanced batteries, auxiliary or ancillary power sources, and electric, hybrid electric, plug in hybrid electric vehicles, and other gaseous and liquid fueled vehicles is helpful.
Employee Job Functions
Employee Job Functions are physical actions and/or working conditions associated with the position. These functions may also constitute essential functions for the job position which the employee must be able to fulfill, with or without accommodation. Information provided below is to help describe the job so that the applicant has a reasonable understanding of the job duties/expectations. An applicant's ability to perform and/or tolerate these actions and conditions will be discussed and workplace accommodations may be made on a case-by-case basis following an individualized assessment of the applicant and other considerations, including but not limited to any governing safety standards.
Fine motor contol (hands); Repetitive work; Visually demanding work; Speech discrimination; Ability to hear audio alarms;Typing/keyboard; Working > 8 hrs./day.
Please Apply Before:
Environmental, Safety and Health Statement
Must be familiar with, and comply with all relevant health and safety requirements. Must be knowledgeable of emergency action policies and procedures, methods for reporting/resolving work practices or conditions to available cognizant professionals.
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INL is a science-based, applied engineering national laboratory dedicated to supporting the U.S. Department of Energy's mission in nuclear energy research, science, and national defense. With 3,800 scientist, researchers and support staff, the laboratory works with national and international governments, universities and industry partners to discover new science and develop technologies that underpin the nation's nuclear and renewable energy, national security and environmental missions.
The Idaho Falls Area
Idaho Falls is conveniently situated near many national treasures such as Yellowstone National Park, Teton National Park, Jackson, WY, etc. For more information about the area, please visit www.visitidahofalls.com and www.visitidaho.org .
Equal Employment Opportunity
Idaho National Laboratory (INL) is an Equal Employment Opportunity (EEO) employer. It is the policy of INL to provide equal employment opportunities to all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
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