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Argonne National Laboratory

Postdoctoral Appointee - Supply Chain Risk Analyst

Posted Yesterday
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In-Office
Lemont, IL, USA
73K-121K Annually
Junior
In-Office
Lemont, IL, USA
73K-121K Annually
Junior
Lead R&D of predictive models and analytical tools to assess and improve domestic and global supply chain resilience for energy technologies. Build a targeted supply chain database, apply advanced analytics to evaluate sourcing strategies and risks, create user-friendly software interfaces and visualizations, engage stakeholders and community groups, and communicate results through reports and publications.
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The Nuclear Technologies and National Security Directorate (NTNS) is seeking a dynamic and passionate Postdoctoral Appointee with strong background in statistics or machine learning to lead an innovative project aimed at enhancing global and domestic supply chain resilience through the development of advanced supply chain analytical tools. The role will require ability to understand and integrate diverse data sets, including trade, political, economic, and social metrics to identify global risks that impact sourcing strategies essential for achieving economic and climate objectives. 

Key Responsibilities:

  • Spearhead the research and development of predictive models and strategic tools designed to support decision making in strengthening both domestic and international supply chains, particularly focusing on energy technologies. 

  • Collaborate on the creation of a comprehensive supply chain database specifically for targeted energy technologies. 

  • Apply advanced analytics to assess and classify domestic and global sourcing strategies, taking into consideration of various risks and uncertainties. 

  • Partner with an interdisciplinary team to support creation of supply chain databases and develop user-friendly software interfaces that enhance data accessibility of data and insight for diverse stakeholders. 

  • Facilitate ongoing communications and foster relationships with a broad array of stakeholders, including community groups, governmental bodies, and private sector entities. 

  • Conduct rigorous analysis and develop models for improving the domestic and global resilience of supply chains for energy technologies 

  • Support stakeholder engagement and community building activities such as townhalls, info sessions and workshops 

  • Communicate research outcomes through scientific and technical reports, peer-reviewed publications, conference papers and presentations. 

What We Offer:  

  • An opportunity to lead groundbreaking research that makes a tangible impact on global and domestic supply chains. 

  • A supportive, collegial environment that encourages innovation and fosters professional growth. 

  • Active participation in a dynamic network of scholars and industry experts committed to addressing critical global challenges through collaboration and innovation. 

Position Requirements

  • This level of knowledge is typically achieved through a formal education in Statistics, Machine Learning, Computer Science, Logistics/Supply Chain, or a related field at the Ph.D. level with zero to five years of employment experience. 

  • Demonstrated experience in leading research initiatives, with a strong track record of publishing in peer-reviewed journals. 

  • Excellent communication skills, capable of crafting and presenting complex information effectively to a variety of audiences. 

  • Ability to work collaboratively in a multidisciplinary team setting. 

  • Commitment to Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.

Desired Knowledge, Skills, and Experience 

  • Proven capability in convergent thinking and systems analysis, drawing on diverse academic backgrounds such as engineering, computer science, statistics, and economics. 

  • Familiarity with energy technologies and associated supply chain risk and challenges.

  • Familiarity with the application of statistics and machine learning techniques in analyzing supply chain risk.

  • Ability to develop and synthesize visualizations to effectively communicate analysis results.

  • Strong programming skills in statistical languages such as R or Python. 

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

The expected hiring range for this position is $72,879.00-$121,465.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here to view Argonne employee benefits!

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.  

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis.  Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements.  Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

HQ

Argonne National Laboratory Lemont, Illinois, USA Office

9700 S. Cass Avenue, Lemont, IL, United States, 60439

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