Graduate (Year-Round) Internship – Digital Twin Development for Biorefinery Processes

The Integrated Carbon Conversion Processes (ICCP) Group within NREL's Catalytic Carbon Transformation and Scale-Up (CCTS) Center has an opening for a Graduate Internship position. The selected candidate will support senior process engineers, modelers, and data scientists in developing a digital twin for an experimental biological and thermocatalytic conversion platform. The goal of the project is to create a virtual representation of key unit operations, enabling real-time monitoring, dynamic simulation, and predictive analytics for biomass and waste conversion to produce biofuels and bioproducts.

The chosen candidate’s responsibilities include:

• Design and implement process models representing biomass conversion, upgrading, and separation units
• Integrate sensor data and historical process data into the digital twin architecture
• Develop simulation tools and dashboards for visualization, control, and scenario analysis
• Contribute to model validation using pilot-scale data and collaboration on experimental feedback loops
• Document assumptions, system architecture, and modeling workflows for reproducibility and team collaboration
• Participate in team meetings and present regular progress updates
• Contribute toward peer reviewed manuscripts and other technical documentation

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Basic Qualifications

Minimum of a 3.0 cumulative grade point average.

Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution. 
Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year.

Graduate: Must be enrolled as a full-time student in a master’s degree program from an accredited institution. 
Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution. 

Please Note:
• Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
• If selected for position, a letter of recommendation will be required as part of the hiring process.
• Must meet educational requirements prior to employment start date.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• The candidate should be currently pursuing or have recently completed a master's degree or be currently enrolled in a Ph.D. program in computational sciences, computational engineering, mechanical engineering, chemical engineering, biological engineering, chemistry, biology, or a related field
• Experience programming in Python and/or C++
• Experience modeling chemical reactors (e.g., using Cantera) and integrating with computational fluid dynamics (CFD) frameworks

Preferred Qualifications

• Experience building techno-economic models using software platforms (e.g., Aspen Plus)
• Exposure to artificial intelligence/machine learning methods for process optimization or anomaly detection
• Experience with digital twin platforms (e.g., AnyLogic, TwinCAT, Siemens Xcelerator)
• Interest in bioprocessing, energy systems, or sustainable technology development.
• Strong problem-solving, communication, and collaboration skills