Postdoctoral Appointee – Artificial Intelligence Applied to Autonomous Coating
- Argonne National Laboratory
- Location: Lemont, USA
- Job Number: 7174201 (Ref #: 416443)
- Posting Date: Aug 28, 2023
- Application Deadline: Open Until Filled
This is an opportunity for a knowledgeable and creative individual to be part of a team using artificial intelligence and high-performance computing to enable autonomous coating manufacturing to support U.S. domestic manufacturing in renewable energy industry, such as fuel cell, hydrogen production, and lithium battery. The scientific goals are to explore the relationship between ink property, coating process, membrane microstructure, and electrode performance, and to use physics-informed artificial intelligence (AI) and edge sensors to improve coating process precision and reliability.
The successful candidate will work closely with researchers at the Applied Materials Division and the Data Science and Learning division of Argonne National Laboratory. The primary responsibilities of the post-doc candidate will be to apply machine learning techniques to achieve defect identification from image and spectrum data and to develop hierarchical learning framework that enables autonomous coating process control. A benefit, ideal candidate will be expected to work closely with domain experts within a multidisciplinary team to leverage emerging computing techniques to solve pressing challenges. Beyond the listed technical development, the candidate is expected to contribute to project reporting and scientific proposal preparation, as well as to present Argonne’s research at peer-reviewed journals and domestic and international conferences.
PhD. in computer science, materials science, chemistry, physics, mathematics, or related engineering disciplines.
Knowledge of deep learning techniques for time-series and image data.
Experience with applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems.
Interest in software development, with particular emphasis on the Python programming language and contributions to open-source scientific software.
Demonstrated scientific productivity, as demonstrated by publications and conference presentations.
A successful candidate must have the ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
Experience in slurry synthesis and rheologic property characterization.
Experience in wet film deposition and drying.
Experience with analyzing large and/or complex datasets.
Knowledge in physics-based modeling such as fluid dynamics or Multiphysics.
Effective oral and written communication skills.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
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