Deep Learning Researcher - PhysicsAI

Experteer Overview In this role you apply deep learning and physics-based simulation to industrial engineering problems, advancing surrogate modeling and generative AI for product design. You will collaborate with application engineers to capture customer needs and drive methods from research to product-ready code. The role focuses on exploring emerging DL tech for mechanical, aerospace, and civil engineering, shaping scalable solutions in Simcenter PhysicsAI. This is a hands-on, impact-driven path in a collaborative team. Pay / Benefits * Identify and assess emerging deep learning technologies for engineering domains (mechanical, aerospace, civil) * Develop and productize promising DL approaches with production-grade code * Evaluate gaps in current genAI capabilities to guide future research directions * Capture customer needs by working with application engineers and specialists Tasks * Master’s or PhD in relevant technical field * Strong theoretical knowledge of deep learning fundamentals * Proficiency with architectures such as transformers, diffusion models, normalizing flows, and Graph Neural Networks (GNNs) * Theoretical knowledge of physics-based simulation (FEA, CFD) * Strong background in PDEs and numerical methods * Experience with mesh-based processing algorithms * Hands-on experience with PyTorch or TensorFlow * Experience working on large, complex code bases * Strong problem-solving skills and ability to communicate technical findings clearly Key requirements * hybrid work model * incentive compensation * health and wellness benefits * global mobility * strong technical peers * career development opportunities

Experteer Overview In this role you apply deep learning and physics-based simulation to industrial engineering problems, advancing surrogate modeling and generative AI for product design. You will collaborate with application engineers to capture customer needs and drive methods from research to product-ready code. The role focuses on exploring emerging DL tech for mechanical, aerospace, and civil engineering, shaping scalable solutions in Simcenter PhysicsAI. This is a hands-on, impact-driven path in a collaborative team. Pay / Benefits * Identify and assess emerging deep learning technologies for engineering domains (mechanical, aerospace, civil) * Develop and productize promising DL approaches with production-grade code * Evaluate gaps in current genAI capabilities to guide future research directions * Capture customer needs by working with application engineers and specialists Tasks * Master’s or PhD in relevant technical field * Strong theoretical knowledge of deep learning aaa Experteer * Proficiency with architectures such as transformers, diffusion models, normalizing flows, and Graph Neural Networks (GNNs) * Theoretical knowledge of physics-based simulation (FEA, CFD) * Strong background in PDEs and numerical methods * Experience with mesh-based processing algorithms * Hands-on experience with PyTorch or TensorFlow * Experience working on large, complex code bases * Strong problem-solving skills and ability to communicate technical findings clearly Key requirements * hybrid work model * incentive compensation * health and wellness benefits * global mobility * strong technical peers * career development opportunities