Argonne National Laboratory Postdoctoral Appointee: Industrial Decarbonization – Process Intensification in Lemont, Illinois
Postdoctoral Appointee: Industrial Decarbonization – Process Intensification
Requisition Number: 410197 Location: Lemont, IL
Functional Area: Research and Development Division: ES-Energy Systems
Employment Category: Temporary 6 Months or Greater Education Required: Doctorate Degree
Level (Grade): 700 Shift: 8:30 - 5:00 Share: Facebook LinkedIn Twitter
The Manufacturing Analysis Group within CEEESA in the Energy Systems Division at Argonne is looking for a postdoctoral appointee to conduct research and analysis in the area of industrial decarbonization, with a focus on systematic process intensification for optimizing next-generation, low-to-zero carbon manufacturing processes. These processes may incorporate alternative energy sources and thermo-chemical energy conversion and storage technologies, grid-integration for demand-response, and carbon capture. The goal of the research is to develop an optimization framework that systematically identifies process configurations that reduce the carbon intensity of these manufacturing processes, while optimizing other performance metrics essential for a feasible and sustainable transition towards industrial decarbonization. This research will focus on carbon-intensive industries like petroleum, chemical synthesis and iron and steel processing.
Specifically, the candidate will combine knowledge of chemical and/or manufacturing process engineering science, computational modeling, and where applicable, machine learning and data-analytic tools to:
- Develop reduced-order, physics-based or data-analytic representations of system sub-components at relevant scales, required to fully describe target industrial manufacturing processes.
- Develop a systematic simulation and optimization framework for exploring novel configurations that reduce the carbon-intensity of the manufacturing process while maximizing other specified performance metrics. This tool may also be used to assess the relative feasibility, performance, anddecarbonization-potentialof specific process configurations.
The candidate will communicate impactful research outcomes through internal and DOE reports, peer-reviewed publications, and conference presentations. The candidate may also support other related projects within the team’s portfolio.
Safety, Security, and Environmental Protection: All activities, as they apply to work performed by self or by personnel under supervision, will be executed in compliance with ES&H and security responsibilities established by Argonne National Laboratory's ES&H policies, Safeguards and Security policies, work rules, and safe practices.
- PhD in chemical engineering, mechanical engineering or any relevant engineering or computational sciences field.
- 0-3 years of experience.
- Experience with scientific computation, with a focus on mathematical optimization.
- Excellent oral and written communication skills at all levels of the organization.
- Background in physical, chemical and computational sciences and/or engineering.
- Experience with mathematical optimization, physics-based computational modeling.
- Experience with modern scientific programming languages (e.g. Python, Julia).
- Knowledge of chemical and/or manufacturing process modeling.
- Knowledge of machine learning, uncertainty quantification, data analytics and visualization.
- Knowledge ofparallel/high-performancecomputing.
- Experience developing tools and datasets for public use.
- Experience working in a multidisciplinary research team environment.
- Experience with writing successful grant proposals.
- Commitment to Argonne’s Core Values: Impact, Safety, Respect, and Teamwork.
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.
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.
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