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Robotics Phd Intern Jobs (NOW HIRING)

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Special Projects Intern [Fall 2026]

San Jose, CA · On-site

$40 - $45/hr

We are looking for a Special Projects Intern to develop robot behaviors and software for external ... Graduate student (Master's or PhD) pursuing a degree in Computer Science, Robotics, Computer ...

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Robotics Phd Intern information

What does a Robotics PhD Intern do?

A Robotics PhD Intern typically works on advanced research and development projects related to robotics, such as designing algorithms, building prototypes, and conducting experiments. They collaborate with senior researchers and engineers, contribute to academic publications, and may present their findings at conferences. The internship is designed to provide hands-on experience in applying theoretical knowledge to solve real-world robotics challenges, often in areas like machine learning, computer vision, or control systems.

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

To thrive as a Robotics PhD Intern, you need advanced knowledge of robotics, machine learning, and algorithm development, usually supported by ongoing doctoral studies in robotics, computer science, or a related field. Proficiency with programming languages such as Python or C++, simulation tools like ROS (Robot Operating System), and relevant research methodologies is typically required. Strong analytical thinking, problem-solving abilities, and effective collaboration and communication skills help interns excel in research teams. These skills and qualities are crucial for driving innovation, contributing to cutting-edge projects, and effectively translating research into practical robotics solutions.

What is the difference between Robotics Phd Intern vs Robotics Engineer?

AspectRobotics Phd InternRobotics Engineer
Required CredentialsPhD candidate or recent PhD graduate in robotics, engineering, or related fieldBachelor's or Master's in robotics, mechanical, electrical, or computer engineering
Work EnvironmentResearch labs, academic institutions, corporate R&D departmentsIndustrial settings, manufacturing, technology companies, startups
Employer & Industry UsageUniversities, research institutions, corporate R&D teamsTech companies, manufacturing firms, automation industries

The main difference between a Robotics Phd Intern and a Robotics Engineer lies in experience, focus, and employment setting. Interns are typically pursuing or have recently completed a PhD and focus on research and development in academic or corporate labs. Robotics Engineers usually hold a bachelor's or master's degree and work on designing, developing, and implementing robotic systems in industrial environments.

What types of projects and daily tasks can a Robotics PhD Intern expect to work on during their internship?

As a Robotics PhD Intern, you will typically engage in cutting-edge research and development projects, often contributing to areas such as computer vision, machine learning, sensor integration, or autonomous navigation. Daily tasks may include designing and running experiments, analyzing data, developing algorithms, and collaborating closely with multidisciplinary teams of engineers and researchers. Interns often present findings in team meetings and participate in code reviews, gaining valuable feedback and exposure to real-world robotics challenges. This hands-on experience is an excellent opportunity to bridge academic research with industry applications, preparing you for future roles in robotics or advanced R&D.
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Infographic showing various Robotics Phd Intern job openings in the United States as of July 2026, with employment types broken down into 12% Internship, 1% As Needed, 50% Full Time, 33% Part Time, 2% Temporary, and 2% Contract. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution.

Research Internship - United States

Flexion Robotics

San Francisco, CA • On-site

Other

Vision

Posted 11 days ago

Job description

About Flexion:

At Flexion, we're building the intelligence layer powering the next generation of humanoid robots. Our mission is to accelerate the transition from fragile prototypes to real-world humanoid deployment. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zurich), and backed by leading international VC firms. In just months, we've gone from our first line of code to deploying real humanoid capabilities.
Fifty of the world's best robotics researchers are already building the future at Flexion's headquarters in Zurich. Among them are Nikita Rudin, David Hoeller, Julian Nubert, and Korrawe Karunratanakul -  scientists who have redefined what humanoid robots can do. Now we are building their counterpart team in the United States, in San Francisco.

The Role:

If you are among the most capable and ambitious early-career robotics researchers, someone who has stared at the limits of what robots can do today and decided that simply wasn't good enough, we want to hear from you.

You will join Flexion's US research team as an intern, take on research problems that matter most, and deploy real solutions on real hardware. You will work directly with a world-class team across two continents on challenges that have no published answers yet. This internship is designed to give exceptional graduate researchers the opportunity to do their highest-impact work in a fast-moving industrial research environment, with a clear path to a full-time Research Scientist role following the internship.

Requirements

Must-haves:

  • Ongoing PhD in Robotics, Machine Learning, or a closely related field, or a recently completed Master's degree with exceptional research output
  • Demonstrated experience deploying learning-based controllers on real robotic hardware, or strong research signal that you can do so quickly

Strong working knowledge in:

  • Reinforcement learning
  • Physics-based simulation (Isaac Gym/Lab, MuJoCo, or equivalent)
  • Python and PyTorch, including training neural networks at scale

Knowledge in at least two of the following:

  • Diffusion models
  • Flow matching
  • Dexterous manipulation
  • Sim-to-real transfer and real-to-sim calibration
  • Whole-body control and loco-manipulation
  • Synthetic data generation for robot learning
  • Vision Language Model Fine-Tuning (SFT and RL-based)
  • Transformer-based 3D Scene Understanding

Benefits

  • Competitive compensation package
  • A front-row seat at one of the world's most ambitious robotics companies
  • An energetic, collaborative team with a relentless bias for action
  • The opportunity to build something no one has ever done in this field -  alongside the world's leading researchers

Apply