Postdoctoral Appointee - Scientific Machine Learning (SciML) and Explainable Artificial Intelligence (XAI)

Argonne National Laboratory

Lemont, IL

Job posting number: #7084885

Posted: September 8, 2021

Application Deadline: Open Until Filled

Job Description

The Mathematics and Computer Science Division at Argonne National Laboratory seeks well-prepared candidates for a postdoctoral position in explainable and interpretable scientific machine learning.

In this role, you will be performing foundational machine learning research in explainability-preserving modeling approaches and automated post hoc explainable methods, and leveraging the developed methods to solve the challenges posed by black-box deep learning methods in scientific applications. The research will also focus on causal learning, geometric machine learning, and probabilistic programming with flexibility on the class of methods pursued based on a wide range of scientific applications such as climate, nuclear physics, fusion science, and distributed infrastructures. You will actively collaborate with computer scientists, mathematicians, and domain scientists and have the opportunity to build an independent research program. Along with having the opportunity to use advanced supercomputers across the Department of Energy computing facilities such as planned Aurora (>50,000 GPUs) exascale system at the Argonne Leadership Computing Facility ( as well as emerging novel AI accelerators from various hardware vendors such as Cerebras, SambaNova, Graphcore, and Groq (

Position Requirements


Recent or soon-to-be-completed PhD in computer science, mathematics, statistics, or a related discipline
Graduate/postgraduate research in machine learning, computer science, and/or mathematical optimization.
Programming experience in Tensorflow, Pytorch, JAX/Flax
Preferred skills:

Experience in causal learning, geometric machine learning, or probabilistic programming
Proposal development
Experience in interdisciplinary research involving computer scientists/mathematicians and discipline scientists
Ability to work well with other laboratories and universities, supercomputer centers and industry
Ability to provide project leadership as well as have collaborative skills

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.

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