How do I apply for the Robot Learning Intern position at Analog Devices and track my application?

We provide a direct link to the official application portal. You can apply directly here . Additionally, you can easily track this and other applications by clicking the bookmark icon to save it to your YGI Kanban board .

What are the working arrangements and expected duration for the Robot Learning Intern role?

This position is a not disclosed, structured as a not disclosed role, with an expected duration of 6 months.

What educational background or degree level is required for the Robot Learning Intern at Analog Devices?

Candidates are generally expected to be holding or pursuing the following degree levels: PhD.

Does Analog Devices provide visa sponsorship or assistance for international applicants?

Regarding visa assistance and sponsorship for this role, the official status is currently listed as: Not disclosed.

Robot Learning Intern

Analog Devices

Found 1 month ago

Location

Limerick, Ireland

Duration (Months)

6 Months

Time

Not disclosed

Work Mode

Not disclosed

Salary

Not disclosed

Visa Help

Not disclosed

Last Verified

1 month ago

Education

Skills & Qualifications

Technical Skills

machine learning
robotics
Planning and control algorithms
A*
MPC
Optimization techniques
linear/nonlinear optimization
deep learning models
PyTorch
Reinforcement Learning
Imitation Learning
foundation models
VLA models
ROS/ROS2
Gazebo
Isaac

Soft Skills

problem solver
intellectually and professionally reward

Job Description

Robot Learning Intern The Dexterous AI Group (DAG) is looking for Robot Learning Engineer Intern to develop core AI technologies for Analog Devices’ future AI robotics with generality and dexterity, beyond the reach of traditional algorithms and system innovations. Responsibilities include: Contribute the development of advanced learning algorithms for general and dexterous robot using the state-of-the-art techniques. Create sandbox simulations, deployable implementations, and evaluation frameworks for algorithm performance and robustness. Contribute to data requirements, data collection setup and procedure, and data curation. Stay abreast of the latest developments in machine learning and robotics from reputable groups.

Requirements

Currently pursuing Ph.D. degree in relevant area
Strong background in machine learning and robotics
experience in: Planning and control algorithms (e.g., A*, MPC). Optimization techniques (e.g., linear/nonlinear optimization). Training deep learning models with PyTorch. Reinforcement Learning and Imitation Learning.

AI & Machine Learning

Robotics & Autonomous Systems

Languages

English

Nice to Haves

foundation models and VLA models
robotics toolkits (e.g., ROS/ROS2, Gazebo, Isaac)
robotic systems and mechanical design

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