INTERNSHIP DETAILS

Biomass Computational Science Intern - Summer 2027

CompanyIdaho National Laboratory
LocationIdaho Falls
Work ModeOn Site
PostedSeptember 29, 2026
Internship Information
Core Responsibilities
The intern will support the development of computational tools and digital models for biomass feedstock preprocessing and handling systems. They will collaborate with scientists and engineers to analyze material behavior and identify engineering solutions to improve process efficiency.
Internship Type
part time
Salary Range
$27 - $41
Company Size
3999
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
In operation since 1949, Idaho National Laboratory is a science-based, applied engineering national laboratory dedicated to supporting the U.S. Department of Energy's missions in energy research, nuclear science and national defense. The world's first usable amount of electricity from nuclear energy was generated here in 1951. At 890 square miles (569,135 acres), the INL Site is roughly 85 percent the size of Rhode Island. In addition to our geographic resources, the lab hosts a variety of unique facilities, including the Advanced Test Reactor National Scientific User Facility. Complementing our nuclear research, the lab has numerous alternative energy and national security programs. Robotics, wind power, high-performance computing, biofuels, critical infrastructure protection, carbon management and advanced vehicle testing are just a few examples of our multifaceted research capabilities. If you are looking for a 21st-century energy or technology career, visit our Careers tab at www.inl.gov. Battelle Energy Alliance manages INL for the U.S. Department of Energy’s Office of Nuclear Energy.
About the Role

Idaho National Laboratory is seeking a motivated intern to support our Physical Process Science and Realization team. As an intern you will support the development of computational tools and digital models for biomass feedstock preprocessing and handling systems. You will also collaborate with INL scientists and engineers to improve understanding of how feedstock properties influence material behavior, processing performance, and product quality, while helping identify engineering solutions that enhance reliability, throughput, and energy efficiency.

Depending on the student’s background and interests, project activities may include scientific software development, data processing and visualization, physics-based simulation, machine learning, or analysis of scientific images and experimental data. This research will help improve understanding of how feedstock properties affect material behavior, preprocessing performance, and product quality while identifying engineering solutions that improve process reliability, throughput, and energy efficiency. Students are not expected to have experience in all the areas listed below. Project assignments will be matched to each student’s technical background, skills, and professional interests. 

This team works a 9x80 schedule onsite at our Idaho Falls campus. Start date and duration of internship vary based on project and student's availability. 

Minimum Qualifications:

  • Enrolled full time in an Undergraduate Degree Program, or Graduate Degree Program majoring in computer science, software engineering, data science, mechanical engineering, civil engineering, chemical engineering, electrical and computer engineering, applied mathematics, or a closely related field
  • Experience operating EFAS or similar sintering systems
  • A minimum overall 3.0 GPA
  • Authorization to work in the U.S. (including CPT and OPT)
  • Current Resume or CV
  • Unofficial Transcripts (include current and completed degree programs)
  • Current class schedule and number of credits

 

Preferred Qualifications:

  • Experience developing, testing, documenting, and maintaining computational research tools using Python or similar programming languages; familiarity with scientific computing, data processing, visualization, software interfaces, workflow automation, version control, or high‑performance computing
  • Experience applying or extending machine‑learning algorithms to experimental or computational datasets; familiarity with common ML libraries, GPU‑accelerated training, physics‑informed ML, or model deployment
  • Experience using computational modeling tools for particle, fluid, or multiphysics simulations; familiarity with discrete element method (DEM), computational fluid dynamics (CFD), CAD tools, or mesh generation
  • Experience developing or applying computational methods to process and analyze scientific images or other experimental datasets; experience improving image quality, identifying/classifying features, measuring structural characteristics, creating 2D/3D visualizations, or automating data‑analysis workflows

 

Compensation:

  • Undergraduate Internships ($26.94/hour - $32.41/hour)
  • Masters Internships ($35.34/hour - $37.73/hour)
  • PhD Internships Pre-Candidacy ($36.83/hour - $39.33/hour)
  • PhD Internships Post-Candidacy ($38.65/hour - $41.29/hour)
  • Multi-Level: Internships are typically multi-level posting and you will be placed at the appropriate level dependent on degree field and level of education.

 

Physical Requirements:

While performing the duties of this classification, the employee is frequently required to stand, walk, sit, stoop, kneel, bend, use hands to handle materials, manipulate tools, type on a keyboard, reach with hands and arms, and operate job-related equipment. The employee must occasionally lift and/or move up to 35 pounds without assistance. Sufficient visual acuity and hearing capacity to perform the essential functions and interact with people is required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. 


Benefits and Relocation

  • Paid holiday time off  
  • Travel reimbursement may be available for eligible interns

At this time, BEA will not sponsor any H1-B visas obtained outside of the United States of America (U.S.A.), including consular visas.

INL is a science-based, applied engineering national laboratory dedicated to supporting the U.S. Department of Energy's mission in nuclear energy research, science, and national defense. With more than 6,300 scientists, researchers, and support staff, the laboratory works with national and international governments, universities and industry partners to change the world's energy future and secure our nation's critical infrastructure.

INL Mission:

Our mission is to discover, demonstrate and secure innovative nuclear energy solutions, other clean energy options and critical infrastructure.

INL Vision:

Our vision is to change the world's energy future and secure our nation's critical infrastructure.

Selective Service Requirements:

To be eligible for employment at INL males born after December 31, 1959 must have registered with the Selective Service System (SSS). For more information see www.sss.gov.

Equal Employment Opportunity:

Idaho National Laboratory (INL) is an Equal Employment Opportunity (EEO) employer. It is the policy of INL to provide equal employment opportunities to all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.

Reasonable Accommodation:

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Other Information:

When applying to positions please provide a resume and answer all questions on the following screens. Applicants, who fail to provide a resume or answer the questions, may be deemed ineligible for consideration.

INL does not accept resumes from third party vendors unsolicited.
Key Skills
PythonMachine learningComputational modelingData processingData visualizationSoftware developmentPhysics-based simulationDiscrete element methodComputational fluid dynamicsCAD toolsHigh-performance computingScientific image analysisWorkflow automationVersion controlBiomass feedstock preprocessing
Categories
Science & ResearchEngineeringTechnologyEnergyData & Analytics
Benefits
Paid holiday time offTravel reimbursement