Postdoctoral Appointee Industrial Decarbonization - Process Intensification - Illinois

Company: Argonne
Your Application: You have not applied yet
Location: USA

Position Description

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, and decarbonization-potential of 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 Laboratorys ES&H policies, Safeguards and Security policies, work rules, and safe practices.

Position Requirements

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 (eg Python, Julia).
Knowledge of chemical and/or manufacturing process modeling.
Knowledge of machine learning, uncertainty quantification, data analytics and visualization.
Knowledge of parallel/high-performance computing.
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.

Work Day: Full Time
Employment type: Permanent Job
Salary: Negotiable

Minimal experience: No experience

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