Postdoctoral Appointee – Applied Artificial Intelligence for Creating Next Generation Materials
- Argonne National Laboratory
- Location: Argonne, IL
- Job Number: 7098645 (Ref #: 413003)
- Posting Date: Apr 7, 2022
- Application Deadline: Open Until Filled
We are seeking a Postdoctoral Appointee to work in the Data Science and Learning division (DSL) of the Computing, Environment, and Life Sciences directorate (CLS) of Argonne National Laboratory. This is an opportunity for a knowledgeable and creative individual to be part of a team using artificial intelligence and high-performance computing to design the next generation of materials.
The primary projects this postdoc will contribute to are finding new routes for chemical storage of hydrogen and the design of copper-carbon composites for enhanced conductivity. Each project will involve close collaboration with a team of domain experts to leverage emerging computing techniques to solve pressing challenges in clean energy and manufacturing.
Primary responsibilities will be to design and implement new techniques for predicting properties of or suggesting new experiments for molecular and metallic materials. While experience in materials engineering is a benefit, ideal candidates will be expected to work together with domain experiments rather than possess all required expertise themselves. Beyond the listed projects, the candidate will be able to contribute to other large-team scientific projects in materials engineering and beyond at Argonne National Laboratory.
Required qualifications and skills:
- A completed or soon-to-be completed (typically within 0-3 years) PhD. in materials science, chemistry, physics, mathematics, computer science or related engineering disciplines.
- Knowledge of deep learning techniques for image and graph 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
- Good scientific productivity, as demonstrated by publications and conference presentations.
- Effective oral and written communication skills.
- Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork
- Experience with analyzing large and/or complex data sets.
Job FamilyPostdoctoral Family
Job ProfilePostdoctoral Appointee
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
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Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's 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.