Experteer Overview In this role you will advance deep learning methods for surrogate modelling and generative AI within Siemens’ PhysicsAI team. You will collaborate with application engineers to translate research into production-grade solutions that tackle industrial design challenges. You will explore disruptive AI technologies, contribute to productization, and influence future method development. This is a chance to shape engineering design processes at scale in a globally impactful software company.Compensaciones / Incentivos
- Identify emerging deep learning technologies and their application to engineering domains
- Prototype and productize promising DL approaches with production-grade code
- Assess gaps in current genAI capabilities to guide future research
- Capture customer needs by collaborating with application engineers and specialistsResponsabilidades




- Advanced theoretical knowledge of deep learning fundamentals
- Strong familiarity with architectures such as transformers, diffusion models, normalizing flows, and Graph Neural Networks (GNNs)
- Proven theoretical background in physics-based simulation (FEA, CFD)
- Strong PDEs and numerical methods knowledge
- Experience with mesh-based processing algorithms
- Hands-on experience with PyTorch or TensorFlow
- Experience working on large, complex codebases
- Strong problem-solving and communication skillsRequisitos principales
- hybrid work model
- health and wellness benefits
- incentive compensation
- global mobility
- equity and inclusion commitment
- career growth opportunities

📌 Deep Learning Researcher - Physicsai (Madrid)
🏢 Siemens
📍 Madrid