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Summer Computer Vision Postdoc Jobs in Colorado (NOW HIRING)

The Role This is a summer internship opportunity in Norwood, MA from June 7, 2027 - August 20, 2026 ... Interest in emerging technologies such as machine learning, computer vision, autonomous systems, or ...

$20 - $60/hr

The Role This is a summer internship opportunity in Norwood, MA from June 7, 2027 - August 20, 2026 ... Interest in emerging technologies such as machine learning, computer vision, autonomous systems, or ...

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Summer Computer Vision Postdoc information

What is a summer computer vision postdoc?

A Summer Computer Vision Postdoc is a temporary research position, typically lasting a few months over the summer, for individuals who have recently earned a PhD in a relevant field such as computer science or electrical engineering. The role focuses on conducting advanced research in computer vision, which involves enabling computers to interpret and process visual information from the world. Postdocs work alongside faculty and research teams, contributing to projects, publishing papers, and gaining additional experience before pursuing faculty positions or industry roles. These positions often emphasize innovation, collaboration, and the practical application of state-of-the-art computer vision techniques.

What are the typical challenges faced by a summer computer vision postdoc working in a research environment?

As a Summer Computer Vision Postdoc, you may encounter challenges such as adapting quickly to new research topics, handling large and complex datasets, and optimizing algorithms for practical performance. Collaboration with interdisciplinary teams is common, requiring clear communication of technical concepts to colleagues from diverse backgrounds. Additionally, you will likely balance multiple projects within a limited timeframe, making effective time management and prioritization essential for success.

What are the key skills and qualifications needed to thrive as a summer computer vision postdoc, and why are they important?

To thrive as a Summer Computer Vision Postdoc, you need a strong background in computer vision, machine learning, and programming, typically supported by a PhD in computer science or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), image processing libraries (like OpenCV), and version control systems (e.g., Git) is essential. Excellent problem-solving abilities, research communication skills, and the ability to collaborate with multidisciplinary teams will make you stand out in this role. These skills ensure you can effectively develop novel algorithms, communicate findings, and contribute to advancing the state of computer vision research.

What are the most commonly searched types of Computer Vision Postdoc jobs in Colorado?

The most popular types of Computer Vision Postdoc jobs in Colorado are:

What job categories do people searching Summer Computer Vision Postdoc jobs in Colorado look for?

The top searched job categories for Summer Computer Vision Postdoc jobs in Colorado are:

What cities in Colorado are hiring for Summer Computer Vision Postdoc jobs?

Cities in Colorado with the most Summer Computer Vision Postdoc job openings:

Postdoctoral Researcher - Autonomous Experimentation for Semiconductor Materials

Golden, CO โ€ข On-site

National Renewable Energy Laboratory
Scientific Research and Development Servicesย โ€ขย 1 - 5K employees

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago


Job description

Posting Title: Postdoctoral Researcher โ€“ Autonomous Experimentation for Semiconductor Materials.

Location: CO โ€“ Golden.

Position Type: Postdoc (Fixed Term).

Hours Per Week: 40.

Working at NLR: NLR is located at the foothills of the Rocky Mountains in Golden, Colorado โ€“ 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, youโ€™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: A postdoctoral research position is available in the Materials Discovery and Development group, focused on autonomous experimentation at the intersection of semiconductor materials research, artificial intelligence methods, and research equipment automation. Our team is developing a next-generation autonomous semiconductor research laboratory as part of the U.S. Department of Energyโ€™s METALLIC platform. The successful candidate will support building closed-loop experimental systems that integrate advanced scientific instrumentation, AI-driven decision-making, data infrastructure, and workflow orchestration. The platform will accelerate the discovery of advanced thin film inorganic semiconductor materials that address critical U.S. supply chain challenges, with particular emphasis on semiconductor technologies involving Ga, Ge, Sc and other critical elements and materials. The successful candidate will also have opportunities to contribute to broader autonomous experimentation initiatives across NLR, including the U.S. Department of Energyโ€™s Genesis Mission projects aimed to accelerate scientific discovery in wurtzite oxide and nitride wide band-gap semiconductor, as well as dielectric, piezoelectric, and ferroelectric materials. As a part of these projects, the successful candidate will develop and apply autonomous experimentation approaches across multiple synthesis and characterization instruments, including vacuum deposition systems such as sputtering, pulsed laser deposition, and molecular beam epitaxy (MBE), as well as advanced property characterization tools, such as photoluminescence, profilometry, J-V, C-V, P-E and other electrical measurements, that complement combinatorial structural (XRD) and compositional (XRF) data.

This position offers an opportunity to develop and deploy new approaches in AI-driven experimentation, scientific software, robotics, and laboratory automation across a large and rapidly evolving set of experimental instruments. As part of this position, the successful candidate will:

  • Design and deploy advanced algorithms and closed-loop workflows for autonomous experimentation on synthesis and characterization instruments.
  • Integrate laboratory instrumentation, data infrastructure, and workflow orchestration systems into scalable autonomous experimentation platforms.
  • Deploy the developed computer vision, robotics, and artificial intelligence methods to solve challenging materials science and semiconductor research problems.
  • Collaborate with materials scientists, engineers, and research technologists to apply autonomous experimentation approaches to other research projects.
  • Proactively diagnose and troubleshoot scientific instrumentation, automation hardware, and software interfaces in accordance with safety practices and operational procedures.

Basic Qualifications:

  • Must be a recent PhD graduate within the last three years.
  • Must meet educational requirements prior to employment start date.

Additional Required Qualifications:

  • Demonstrated hands-on proficiency in Python, including the ability to independently design, implement, understand, debug, and maintain scientific software without reliance on AI-assisted coding tools.
  • Proven knowledge of modern software development practices, including Git-based version control, modular software design, testing, and documentation, is required.
  • Prior experience in developing software for scientific instrumentation, laboratory automation, experimental control, or related hardware applications, and its integration with scientific objectives into robust experimental workflows.
  • Experience with machine learning, statistical modeling, optimization algorithms, or data-driven scientific methods, such as active learning, Bayesian optimization, design of experiments, uncertainty quantification, or related methods.
  • Basic knowledge of materials science, inorganic chemistry, semiconductor physics, vacuum-based thin film processing and characterization methods, composition/structure/property relations, and experimental laboratory equipment.

Preferred Qualifications:

  • Preferred semiconductor materials research qualifications:
    1. Prior hands-on experience developing autonomous or closed-loop experimental laboratory instruments, including high-throughput and combinatorial experiments.
    2. Experience with vacuum-based thin-film synthesis and characterization equipment, such as PVD, PLD or MBE systems, electrical probe stations, photoluminescence instruments, optical microscopes, or related scientific instrumentation.
    3. Knowledge of inorganic thin films and semiconductor materials, particularly oxides, nitrides, wide band-gap semiconductors and dielectrics, or related material systems.
  • Preferred autonomous experimentation qualifications:
    1. Experience with databases, scientific data pipelines, or experimental data management.
    2. Experience deploying scientific software across networked Linux and/or Windows systems in a plus.
    3. Experience implementing feedback control systems, state machines, fault handling, or other control logic for automated experimental systems.
    4. Experience with robotics, motion control, machine vision, or robotic system integration in a plus.
  • Preferred specific software and hardware qualifications: Experience integrating and controlling scientific instrumentation through software APIs, instrument command sets (e.g., SCPI), industrial communication protocols (e.g., Modbus RTU/TCP), and interoperability standards (e.g., OPC UA). Experience with distributed systems and messaging architectures (e.g., NATS, MQTT, ZeroMQ, or similar publish/subscribe and message-oriented systems). Experience with PLC programming using IEC 61131-3 languages, particularly Structured Text (ST) and Ladder Diagram (LD); experience with Red Lion Graphite Edge Controllers and Crimson software is a plus.

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): $76,600 โ€“ $126,400.

NLR takes into consideration a candidateโ€™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 employeeโ€™s salary history will not be used in compensation decisions.

Benefits Summary:

  • medical, dental, and vision insurance
  • short-term disability insurance*
  • pension benefits*
  • 403(b) Employee Savings Plan with employer match*
  • life and accidental death and dismemberment (AD&D) insurance
  • personal time off (PTO) and sick leave
  • paid holidays

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. *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.

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.

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: 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.

National Laboratory of the Rockies (NLR) is the U.S. Department of Energy's primary national laboratory for critical minerals, energy innovation, and energy security. With locations in Golden and Boulder, Colorado, Fairbanks, Alaska, and a satellite office in Washington, D.C., NLR bridges foundational research with practical applications to develop and bring to scale new energy materials and technologies that lower energy costs, drive economic growth, and deliver abundant and reliable energy. NLR is subject to Department of Energy (DOE) access restrictions. All candidates must be authorized to access the facility per DOE rules and guidance within a reasonable time frame for the specified position in order to be considered for an interview and for hiring. DOE rules for site access during the interview process depend on whether the candidate is interviewed on-site, off-site, or via telephone or videoconference. 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. Additionally, DOE contractor employees are prohibited from participating in certain Foreign Government Talent Recruitment Programs (FGTRPs). If a candidate is currently participating in an FGTRP, they will be required to disclose their participation after receiving an offer of employment and may be required to disengage from participation in the FGTRP prior to commencing employment. Any offer of employment is conditional on the ability to obtain work authorization and to be granted access to NLR by the Department of Energy (DOE).

We also hope you will learn more about NLR, visit our Careers site, and continue to search for job opportunities at the lab.

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