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Internship German Machine Learning Jobs in Colorado

We are seeking a German intern/trainee (Praktikant - w/m/d) for our US offices. The internship will ... We keep our employees current by supplying cutting-edge technology and access to learning ...

Past example internship projects include machine learning development, automating current manual processes, infrastructure provisioning, and outer API servicing. PNC looks for interns to bring a ...

Familiarity through former internships, coursework or research with machine learning or AI, APIs, backend development COMPENSATION $17-25/hour Note that interns do not qualify for benefits or equity ...

$50/hr

Position Summary Sony AI is seeking research interns who are passionate about ML-based technologies ... Strong analytical and programming skills in deep learning using frameworks and tools for machine ...

$50/hr

Position Summary Sony AI is seeking research interns who are passionate about ML-based technologies ... Strong analytical and programming skills in deep learning using frameworks and tools for machine ...

Showing results 21-40

Internship German Machine Learning information

What is an internship German machine learning?

An Internship German Machine Learning is a temporary training position typically offered by companies or research institutions in Germany, focusing on practical experience in machine learning. Interns work on real-world projects involving data analysis, algorithm development, and model implementation under supervision. These internships help students or recent graduates gain hands-on skills, industry exposure, and networking opportunities in the rapidly growing field of artificial intelligence and machine learning.

What is the difference between Internship German Machine Learning vs Data Scientist German?

AspectInternship German Machine LearningData Scientist German
Required CredentialsBasic programming, coursework in MLAdvanced degree in data science, statistics, or related
Work EnvironmentInternship setting, learning-focusedFull-time, project-driven
Industry UsageEntry-level roles, training programsProfessional roles, decision-making

Internship German Machine Learning positions are typically entry-level, focusing on learning and skill development, often requiring basic programming and coursework. Data Scientist German roles are more advanced, requiring higher education and experience, with responsibilities in analyzing data and building models. The internship provides a stepping stone into the data science field, while the data scientist role involves applying expertise to solve complex problems.

What types of projects can I expect to work on during a German machine learning internship?

As a German Machine Learning intern, you'll typically assist with real-world projects such as developing and testing machine learning models, preprocessing datasets, and supporting the implementation of AI solutions in both German and international contexts. You may also help with data analysis, model evaluation, and documentation, often collaborating with data scientists and engineers. These projects provide hands-on experience with industry-standard tools and workflows, helping you build practical skills and a strong professional network.

What are the key skills and qualifications needed to thrive as an internship German machine learning?

To thrive as an Internship German Machine Learning, you need a solid understanding of machine learning concepts, programming skills in Python, and progress toward a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, and data analysis libraries, as well as experience using version control systems like Git, is typically required. Strong analytical thinking, problem-solving ability, and effective communication—especially in both English and German—help you collaborate within diverse teams. These skills and qualifications are essential for successfully contributing to machine learning projects and adapting to the fast-evolving tech industry.

What are popular job titles related to Internship German Machine Learning jobs in Colorado?

For Internship German Machine Learning jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Internship German Machine Learning jobs?

Cities in Colorado with the most Internship German Machine Learning job openings:

Infographic showing various Internship German Machine Learning job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

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

The National Renewable Energy Laboratory (NREL)

Golden, CO • On-site

$44K - $71K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 25 days ago


Job description

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

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

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: $44,500 - $71,200
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
E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.