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Computational Modeling Intern Jobs in Colorado (NOW HIRING)

Computational Modeling Intern information

What are some common challenges faced by Computational Modeling Interns during their internship?

Computational Modeling Interns often encounter challenges such as adapting to complex simulation software and learning the specific coding standards used by their team. They may also need to balance multiple projects while ensuring the accuracy and reproducibility of their models. Collaboration with researchers and engineers is frequent, so strong communication skills are important to effectively interpret data and incorporate feedback. These challenges provide valuable learning opportunities and help interns develop a strong foundation for a future career in computational modeling.

What are the key skills and qualifications needed to thrive as a Computational Modeling Intern, and why are they important?

To thrive as a Computational Modeling Intern, you generally need a solid background in mathematics, physics, or engineering, along with proficiency in programming languages like Python or MATLAB. Familiarity with simulation software, data analysis tools, and version control systems such as Git is typically required. Strong analytical thinking, problem-solving abilities, and clear communication skills help interns excel when interpreting results and collaborating with research teams. These skills and qualities are essential for efficiently developing, testing, and refining computational models that drive innovation and research progress.

What does a Computational Modeling Intern do?

A Computational Modeling Intern assists in developing and running computer-based simulations to analyze scientific, engineering, or business problems. They work with specialized software and programming languages to build models that predict outcomes, test hypotheses, or optimize processes. Interns often collaborate with experienced researchers or engineers, interpret simulation results, and help document findings. This role provides valuable hands-on experience with computational tools and methodologies used in various industries.

What is the difference between Computational Modeling Intern vs Data Analyst Intern?

AspectComputational Modeling InternData Analyst Intern
Required CredentialsUndergraduate or graduate in STEM, programming skillsUndergraduate or graduate in related field, analytical skills
Work EnvironmentResearch labs, tech companies, academiaBusiness, finance, tech firms, research institutions
Employer & Industry UsageResearch projects, product development, simulationsData analysis, reporting, decision support

Computational Modeling Interns focus on developing and applying computational models and simulations, often requiring programming and mathematical skills. Data Analyst Interns primarily analyze datasets to extract insights, supporting business decisions. While both roles involve data handling, the Modeling Intern emphasizes simulation and algorithm development, whereas the Data Analyst Intern concentrates on data interpretation and reporting.

What are popular job titles related to Computational Modeling Intern jobs in Colorado? For Computational Modeling Intern jobs in Colorado, the most frequently searched job titles are:
Infographic showing various Computational Modeling Intern job openings in Colorado as of July 2026, with employment types broken down into 70% Full Time, 28% Part Time, and 2% Contract. Highlights an 71% Physical, 2% Hybrid, and 27% Remote job distribution.
Post Undergraduate/Graduate (Year-Round) Intern - Molecular Biology

Post Undergraduate/Graduate (Year-Round) Intern - Molecular Biology

The National Renewable Energy Laboratory (NREL)

Golden, CO • On-site

$39K - $63K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 12 days ago


Job description

Posting Title
Post Undergraduate/Graduate (Year-Round) Intern - Molecular Biology
Location
CO - Golden
Position Type
Intern (Fixed Term)
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The RRES Center at NLR has an opening for a full-time post undergraduate/graduate internship within the Synthetic Biology and Bioconversion group.
Responsibilities for this intern will focus on metabolic engineering and synthetic biology to generate, screen, and optimize engineered bacterial strains for production of renewable fuels and chemicals from various biomass-derived intermediates. In collaboration with postdoctoral researchers and research scientists, the intern will engineer strains to validate physiological hypotheses generated by predictive models and/or genome-scale library screens.
In addition, the successful candidate will have the following:
  • Excellent organizational skills, including contemporary laboratory notebook documentation
  • Attention to detail
  • Proficient communication skills, including the ability to succinctly communicate scientific findings to peers
  • Critical thinking skills, including the ability to formulate hypotheses and interpret results
  • Ability to maintain a clean lab space with utmost attention to safety
  • Demonstrated ability to work safely with minimal supervision

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
  • Demonstrated experience in molecular biology, including DNA cloning and transformation.
  • Demonstrated experience in microbiology, including sterile techniques.
  • Experience with computational data analysis, e.g., skills in Python or R.

Preferred Qualifications
Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: / Annual Salary Range: $39,600 - $63,400
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
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.
* Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR 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.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
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