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Lemont, IL 60439
The incumbent will conduct basic research in the area of data driven optimization and machine learning with a focus on time dependent methods as applied to weather forecasting, climate forecasting, and state estimation. The position involves balance between documentation, method designing, method prototyping, and validation and requires interaction with a diverse team of scientists and environmental and electrical engineers. The incumbent will be part of the of these positions are in conjunction with the MACSER project (Multifaceted Mathematics for Rare, High-Impact Events in Complex Energy and Environment Systems) https://www.mcs.anl.gov/MACSER : a multi-institution team that includes computational mathematicians, statisticians, climate model experts, engineers, and computer scientists.
Conducts basic research in machine learning and state estimation. Reports on results of research by publishing scholarly papers in scientific journals.
Develops methods for the machine learning solution of applied computational problems on power grid and environmental science on scalable parallel computers. Assures that innovative software embodies newly discovered techniques.
Collaborates with scientists within the division, and with scientists at Argonne on mathematical and computer science issues.
This position requires in a Master’s Degree in a related field.
Long-Term (Fixed Term)
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, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
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