Utilization of Physical AI for Fast and Efficient Implementation of Robotic-Assisted Processes in Diagnostic and Pharmaceutical Raw Material Production (m/f/d)

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The implementation of robotics and automation in industrial environments currently requires high investment, significant engineering effort, and extensive setup times. Consequently, automation is often only economically viable for processes characterized by high repetition, low uniformity, low variance, or strict requirements for product and personal protection.

• Solid understanding of Machine Learning (ML) and Deep Learning (DL) architectures
• Familiarity with concepts like Reinforcement Learning (RL), Imitation Learning (Learning from Demonstration), or Physics-Informed Neural Networks (PINNs)
• Experience applying AI to physical systems or hardware

• Strong foundation in robot kinematics, dynamics, and control
• Experience with robotic frameworks, primarily ROS / ROS2 (Robot Operating System)

• Advanced programming skills in Python and/or C++.Experience with ML frameworks such as PyTorch, TensorFlow, or JAX.Familiarity with simulation environments (e.g., Isaac Sim, MuJoCo, Gazebo)
• Domain Knowledge & Soft Skills

• 3,750 € salary per month for a full-time
• The possibility of accommodation in the Roche Boarding House or convenient transport connections to Munich with the Roche Shuttle

Your Application:

Please upload your Curriculum vitae specific to this position.

Start: As of January 2027 or according to the agreement for a period of 3 years.

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