Argonne National Laboratory Postdoctoral Appointee – Machine Learning for Battery Performance and Process Optimization in Lemont, Illinois
Postdoctoral Appointee – Machine Learning for Battery Performance and Process Optimization
Requisition Number: 407129 Location: Lemont, IL
Functional Area: Research and Development Division: AMD-Applied Materials Division
Employment Category: Temporary 6 Months or Greater Education Required: Doctorate Degree or equivalent
Level (Grade): 700 Shift: 8:30 - 5:00 Share: Facebook LinkedIn Twitter
This is an opportunity for a knowledgeable and creative individual to participate in a multidisciplinary, cutting edge project on predicting the lifetimes and degradation mechanisms of Li-ion batteries using a variety of artificial intelligence techniques. The project aims to leverage materials science, deep learning, and traditional machine learning to better understand and predict quantities of interest for a variety of battery designs, chemistries, and cycling protocols.
The successful candidate will work in the Applied Materials division of the Energy and Global Security directorate developing mathematical models, software, and methodology for predicting the cycle lives of batteries and autonomously categorizing batteries based on their behavior. Beyond this primary project, the successful candidate will participate in other multi-disciplinary projects, including one using active learning to optimize nanoparticle synthesis via flame spray pyrolysis.
PhD. in materials science, chemistry, physics, mathematics, computer science or related engineering disciplines.
A successful candidate will have the following:
- Knowledge of battery design, electrochemistry, and degradation mechanisms
- Experience with applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems.
- Good experience with software development, including scripting, Python, and high level programming languages
- Good scientific productivity, as demonstrated by publications and conference presentations.
- Desirable skills: Effective oral and written communication skills.
- Experience with analyzing large and/or complex data sets.
As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486.1. You will be asked to disclose any such participation in the application phase for review by Argonne’s Legal Department.