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Phd Wearable Sensor Intern Jobs in Colorado (NOW HIRING)

An educational platform on tribology -- the science of friction, wear and lubrication Who is it for ... Degrees at the Master or PhD level are preferred.Experience * 5-7+ years of experience applying ...

Phd Wearable Sensor Intern information

What does a PhD wearable sensor intern do?

A PhD Wearable Sensor Intern typically works on the research and development of advanced sensor technologies that can be integrated into wearable devices. Their responsibilities may include designing experiments, collecting and analyzing physiological data, developing algorithms to process sensor data, and collaborating with multidisciplinary teams. The internship is often aimed at leveraging the intern’s expertise to solve complex problems in wearable health monitoring, activity recognition, or user interaction. This hands-on experience helps bridge academic research with real-world applications in the wearable technology industry.

What types of projects might a PhD wearable sensor intern typically work on during their internship?

As a PhD Wearable Sensor Intern, you can expect to work on interdisciplinary projects that involve designing, prototyping, and testing advanced wearable sensor technologies. You may contribute to both hardware development and data analysis, collaborating closely with engineers, data scientists, and product teams to address real-world health or performance monitoring challenges. Interns often have the opportunity to publish research findings, present at internal meetings, and gain exposure to the product development lifecycle. This role provides valuable experience in both academic research and industry-driven innovation.

What are the key skills and qualifications needed to thrive as a PhD wearable sensor intern, and why are they important?

To thrive as a PhD Wearable Sensor Intern, you typically need a strong background in electrical engineering, biomedical engineering, or a related field, along with experience in sensor design and data analysis. Familiarity with programming languages (such as Python or MATLAB), signal processing tools, and hardware prototyping platforms is often required. Strong problem-solving abilities, attention to detail, and effective communication skills help interns collaborate with multidisciplinary teams and articulate research findings. These skills are crucial for advancing sensor technologies and delivering impactful research outcomes in wearable health monitoring.

What is the difference between Phd Wearable Sensor Intern vs Phd Biomedical Engineer?

AspectPhd Wearable Sensor InternPhd Biomedical Engineer
CredentialsPhD or pursuing PhD in engineering, computer science, or related fieldsPhD in biomedical engineering, electrical engineering, or related fields
Work EnvironmentResearch labs, tech companies, startups focusing on wearable techHospitals, research institutions, medical device companies
Industry UsageInternship roles in wearable sensor development and testingDesign, develop, and improve biomedical devices and systems

The Phd Wearable Sensor Intern typically focuses on research and development of wearable sensor prototypes during an internship, often in a tech or startup environment. In contrast, a Phd Biomedical Engineer usually works on designing and improving medical devices in a more permanent role within healthcare or medical device companies. Both roles require advanced degrees but differ mainly in their scope, responsibilities, and work settings.

What job categories do people searching Phd Wearable Sensor Intern jobs in Colorado look for?

The top searched job categories for Phd Wearable Sensor Intern jobs in Colorado are:

What cities in Colorado are hiring for Phd Wearable Sensor Intern jobs?

Cities in Colorado with the most Phd Wearable Sensor Intern job openings:

Infographic showing various Phd Wearable Sensor Intern job openings in Colorado as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

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

Golden, CO • On-site

The National Renewable Energy Laboratory (NREL)
Scientific Research and Development Services • 1 - 5K employees

$44K - $71K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 6 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
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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.