Flexion Robotics
Internship - Robotics Manipulation(m/w/x)
Full-timeInternshipOn-site
Zürich
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FLFlexion Robotics
Internship - Humanoid Motion Generation (Diffusion or Flow Matching)(m/w/x)
Zürich
Full-timeInternshipOn-site
AI/ML
Nejo AI Summary
Generating whole-body trajectories for humanoid robots using diffusion models. Master's or PhD in CS, Robotics, or ML required. Work on cutting-edge perception and interaction.
Requirements
- Pursuing Master's or PhD in CS, Robotics, ML, or related field
- Experience in diffusion models/flow matching or learning-based trajectory generation
- Familiarity with generative modeling for time series data
- Excellent Python and PyTorch skills
- Strong analytical and problem-solving skills
- Ability to implement state-of-the-art methods from literature
- Preferable: autonomous research/project work in human motion generation, robotic imitation learning, or ego-centric action prediction
- Experience in robotics (plus)
- Experience with simulation environments (plus)
- Experience with multi-modal generative models (plus)
- Experience with finetuning foundation models for actions/kinematics (plus)
Tasks
- Work at the intersection of generative whole-body trajectory generation and 3D environment perception
- Utilize diffusion models, flow matching, and/or auto-regressive models for trajectory generation
- Push boundaries of humanoid robot perception and interaction
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- diffusion models
- flow matching
- generative modeling
- foundation models
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Flexion Robotics and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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FLFlexion Robotics
Internship - Humanoid Motion Generation (Diffusion or Flow Matching)(m/w/x)
Zürich
Full-timeInternshipOn-site
AI/ML
Nejo AI Summary
Generating whole-body trajectories for humanoid robots using diffusion models. Master's or PhD in CS, Robotics, or ML required. Work on cutting-edge perception and interaction.
Requirements
- Pursuing Master's or PhD in CS, Robotics, ML, or related field
- Experience in diffusion models/flow matching or learning-based trajectory generation
- Familiarity with generative modeling for time series data
- Excellent Python and PyTorch skills
- Strong analytical and problem-solving skills
- Ability to implement state-of-the-art methods from literature
- Preferable: autonomous research/project work in human motion generation, robotic imitation learning, or ego-centric action prediction
- Experience in robotics (plus)
- Experience with simulation environments (plus)
- Experience with multi-modal generative models (plus)
- Experience with finetuning foundation models for actions/kinematics (plus)
Tasks
- Work at the intersection of generative whole-body trajectory generation and 3D environment perception
- Utilize diffusion models, flow matching, and/or auto-regressive models for trajectory generation
- Push boundaries of humanoid robot perception and interaction
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- diffusion models
- flow matching
- generative modeling
- foundation models
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Flexion Robotics and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
Flexion Robotics
Industry
IT
Description
Flexion builds the intelligence layer for next-gen humanoid robots, accelerating their real-world deployment.
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