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English
$
USD
I will build physics informed neural networks and sciml models
MLOPs ML GNNs PINNs RnDs
ML || MLOPs || Data Engineering || Agentic AI || Knowledge Distillation || GNNs || Physics-Informed NNs || n8n Workflow Automation || RL PPO DPO MARL || Pytorch || Tensorflow || Rust || https://github...
Level 1
Has met certain performance criteria and shows strong potential in the marketplace.
About this Gig
Struggling to couple physical laws with deep learning for your thesis? I specialize in translating complex differential equations (Navier-Stokes, heat equations, ODEs/PDEs) into robust training architectures.
What I Deliver: Clean, heavily documented PyTorch/DeepXDE code, custom loss functions enforcing boundary/initial conditions, loss convergence plots, and a comprehensive README explaining the architecture.
