Undergraduate/Post-Undergraduate (Summer) Intern – Computational Modeling of Catalytic Bioenergy Processes

National Renewable Energy Laboratory

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About The Position

The Computational Modeling group in the BEST directorate at the National Laboratory of the Rockies (NLR) is seeking an summer undergraduate or post-undergraduate research intern to perform computational modeling and data analysis to enable optimization and scale-up of catalytic bioenergy processes. The intern will work closely with other computational scientists and experimentalists to perform, analyze, and validate simulations of biomass and other feedstocks undergoing catalytic and thermochemical conversion processes using process scale models. Responsibilities include: Performing simulations using high-fidelity Computational Fluid Dynamics (CFD) and reduced order models of transport and reactive processes within catalytic reactor systems Implementing kinetic schemes into reduced order models and performing optimization routines to fit kinetic parameters Analyzing validation experiments Programming scripts to analyze results from simulations Providing regular written and oral progress updates at project meetings Working safely and independently in a laboratory setting Planning and executing research in collaboration with other researchers Contributing to the creation of technical reports and peer-reviewed publication Working effectively in a large, multidisciplinary, multi-institutional team of engineers and scientists. The successful candidate will: Engage with a multi-disciplinary team of scientists across multiple national laboratories Gain experience in a range of computational modeling and data analysis techniques, including FEM/FVM and reduced order modeling using software packages that are relevant to the field Develop practical research skills through industrially relevant applications of computational models for chemical processes Contribute to high-impact energy research Maintain professionalism and an environment of mutual respect in all communication and interactions with fellow staff and collaborators

Requirements

• 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.
• Currently enrolled in or recently graduated from a bachelor’s degree program in Computer Science, Chemical Engineering, or a related field
• Demonstrated programming skills in Python and libraries such as: SciPy, Matplotlib, NumPy
• Strong motivation to contribute to high-impact research
• Demonstrated ability to collaborate and work efficiently within a team
• Excellent writing and communications skills, with the ability to present technical results to a wide audience

Nice To Haves

• Current junior or senior level student or recent graduate of a bachelor’s degree in Computer Science, Chemical Engineering, or a related field
• Familiarity with Linux environments and high-performance computing
• Knowledge of or experience using FEM and/or FVM software including OpenFOAM, MFIX, COMSOL, Fluent, or similar (CFD packages)
• Knowledge of or experience with performing and analyzing reactor-scale simulations
• Knowledge of or experience with catalytic processes (modeling or experimental)
• Knowledge/experience with machine learning i.e. tensor flow/PyTorch

Responsibilities

• Performing simulations using high-fidelity Computational Fluid Dynamics (CFD) and reduced order models of transport and reactive processes within catalytic reactor systems
• Implementing kinetic schemes into reduced order models and performing optimization routines to fit kinetic parameters
• Analyzing validation experiments
• Programming scripts to analyze results from simulations
• Providing regular written and oral progress updates at project meetings
• Working safely and independently in a laboratory setting
• Planning and executing research in collaboration with other researchers
• Contributing to the creation of technical reports and peer-reviewed publication
• Working effectively in a large, multidisciplinary, multi-institutional team of engineers and scientists

Benefits

• Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match; and sick leave (where required by law).
• NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component.
• Some positions may be eligible for relocation expense reimbursement.
• Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Number of Employees: 1,001-5,000 employees