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ICBMS-3d.FAB, CNRS – University of Lyon

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Postdoc in Physics-Informed Neural Networks for Cognitive Additive Manufacturing ICBMS-3d.FAB research group, CNRS / Université Claude Bernard Lyon 1 in France

Degree Level

Postdoc

Field of study

Computer Science

Funding

18-month postdoctoral position with salary depending on experience.

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Country

France

University

ICBMS-3d.FAB, CNRS – University of Lyon

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Keywords

Computer Science
Mechanical Engineering
Materials Science
Deep Learning
Mathematics
Industrial Engineering
Computational Physics
Rheology
Additive Manufacturing
Digital Twin Technology
Granular Physics
Physics
Applied Mathematic
Robot Kinematics
ML

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About this position

Postdoc opportunity at ICBMS-3d.FAB (CNRS / Université Claude Bernard Lyon 1) in Villeurbanne (Lyon), France.

The project focuses on developing a physics-informed neural network (PINN) model for cognitive additive manufacturing, combining experimental data, process monitoring, and numerical simulation. The work includes designing PINNs that integrate rheology, granular physics, and robotic kinematics, and contributing to an AI-driven cognitive slicer and digital twin for the Dynamic Molding process.

The postdoc will collaborate with industrial partners and a dedicated data scientist. Strong skills in Python, PyTorch or TensorFlow, and physics-based simulation are required. Experience with PINNs and knowledge of additive manufacturing or robotics are a plus.

Eligibility: applicants should hold a PhD in AI / Machine Learning / Computational Physics / Applied Mathematics or a related field.

Duration and funding: 18 months, with salary depending on experience.

How to apply: send a resume and cover letter to [email protected] and [email protected].

Funding details

18-month postdoctoral position with salary depending on experience.

What's required

PhD in AI, Machine Learning, Computational Physics, Applied Mathematics, or a related field. Strong experience with deep learning frameworks such as PyTorch or TensorFlow, physics-based simulation, and Python is required. PINN experience and knowledge of additive manufacturing or robotics are considered a plus.

How to apply

Send a resume and cover letter by email to [email protected] and [email protected].

More information can be found here

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