Research Intern - Machine Vision

  • National Renewable Energy Laboratory
  • Colorado, USA
  • Jul 17, 2019
Internship Aerospace engineering Astronomy Biology Computer Science Chemical engineering Engineering Health Science Life Science Mathematics Medical Sciences Chemistry Civil engineering Physics Psychology Social Science Teaching/Academics Technology Veterinary medicine


The National Renewable Energy Laboratory (NREL) in Golden, Colorado, is the nation's primary laboratory for research, development, and deployment of renewable energy and energy efficiency technologies. The National Bioenergy Center at NREL has an opening for a part-time Research Intern. This position supports the National Bioenergy Center’s mission to develop biomass conversion processes focusing on the chemical and mechanical treatment of lignocellulosic biomass for production of renewable fuels and chemicals. The intern will assist with the selection of methodologies and will build, train, and test machine vision models for classification and measurement of biomass feedstock particle size, shape, aspect ratios, etc. Opportunity to publish work results is also available.

Primary duties include:

  • Assist with the selection of and construction of artificial intelligence (AI) methods and models for image classification and particle property analysis.
  • Implement AI methods for biomass feedstock classification and/or particle property measurement in Python code and perform training, testing, and development of models using existing image dataset.
  • Implement image segmentation and measurement methods in Python code and assess performance for biomass particle property analysis.
  • Co-author at least one manuscript detailing research and results for a peer-reviewed journal..

Basic Qualifications

  • Must be a current graduate-level student studying Computer Science or a closely related field.
  • Must be enrolled as a full-time student in a degree granting program, or graduated in the past 12 months from an accredited institution. Internship period cannot exceed 12 months past graduation. Minimum of a 3.0 cumulative grade point average.

Please Note: You will need to upload unofficial transcripts and a letter of recommendation as part of the application process.

Additional Qualifications

Must have experience with or currently studying AI techniques, including use of deep neural networks. Must currently be an expert in Python programming language and be proficient with associated modules including Numpy, Pandas, and TensorFlow/Keras. Must be able to effectively communicate scientific results, both written and oral, and can work effectively in a large, multidisciplinary team of engineers, chemists, and technicians.

Preferred Qualifications

Experience with or studying machine vision / automated image analysis. Other preferred qualifications include:

  • Experience with digital photography cameras and intricate knowledge of associated computer file type structures (jpeg, raw).
  • Familiarity with convolutional neural networks (CNN).
  • Excellent technical writing, interpersonal, and communication skills.
  • Ability to work independently and in teams.
  • Dedicated to a safe and clean work environment. 

Submission Guidelines

Please note that in order to be considered an applicant for any position at NREL you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.

EEO Policy

NREL is dedicated to the principles of equal employment opportunity. NREL promotes a work environment that does not discriminate against workers or job applicants and prohibits unlawful discrimination on the basis of race, color, religion, sex, national origin, disability, age, marital status, ancestry, actual or perceived sexual orientation, gender identity, or veteran status, including special disabled veterans. 

NREL validates right to work using E-Verify. NREL will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee’s Form I-9 to confirm work authorization.

Experience level of the applicant we want

College / Sixth form