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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

11Open Positions

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Intern: Software Engineer, AI-enabled Robotic and Dexterous Manipulation Research

Intrinsec
Found 1 month ago
Location
Munich, Germany
Duration (Months)
3 Months
Time
Not disclosed
Work Mode
On-site
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • PhD
  • Master

Skills & Qualifications

Technical Skills

  • Python
  • Jax
  • Pytorch
  • machine learning for robotics
  • reinforcement learning
  • vision-language-action models
  • sim-to-real transfer learning
  • imitation learning
  • foundation models for robotics
  • robot motion control
  • kinematics
  • dynamics

Soft Skills

  • Enthusiasm for experimenting with robot hardware

Job Description

As an Intern in AI-enabled Robotic Manipulation Research you will experiment with novel robotics capabilities that have an impact on real-world applications in manufacturing. You will work alongside a team of researchers and engineers developing features and conducting experiments for machine learning approaches to robot manipulation. You bring in thorough knowledge in robot learning, excitement for getting robot hardware and experiments to run, and solid coding skills. How your work moves the mission forward * Contribute to experiments for novel, AI-enabled and sensor-guided manipulation capabilities. * Evaluate new, prototypical approaches on manipulation scenarios for industrial manufacturing. * Extend existing manipulation capabilities in our stack and improve features related to learning and robot control. * Collaborate with researchers and colleagues across three continents to bring solutions to the real world.

Requirements

  • PhD student in Computer Science, Robotics or related field, or master's student with robotics lab experience.
  • Programming experience in Python (ideally Jax or Pytorch skills).
  • Knowledge and first experience in machine learning for robotics in one or more areas like reinforcement learning, vision-language-action models, sim-to-real transfer learning, imitation learning and/or foundation models for robotics.
  • Enthusiasm for experimenting with robot hardware, ideally prior experience.
  • Basic knowledge of robot motion control, kinematics, dynamics.
  • Ideally, experience in controlling robot motion and/or applying learned models to motion.

Related Field

  • Software Engineering

Related Subfield

  • AI/ML/GenAI Engineering

Languages

  • English

Nice to Haves

  • experience in controlling robot motion
  • applying learned models to motion
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