> Markdown version of [/jobs/ext/2019416-deep-learning-researcher-physicsai](https://www.wearedevelopers.com/jobs/ext/2019416-deep-learning-researcher-physicsai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Deep Learning Researcher - PhysicsAI - **Company:** Siemens Plc - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Artificial Neural Networks, Computational Fluid Dynamics, Data Normalization, Tensorflow, Pytorch, Deep Learning, Information Technology, Production Code - **Published:** August 11, 2026 - **Apply:** https://eu.experteer.com/career/view-jobs/deep-learning-researcher-physicsai-london-grossbritannien-58877243 ## About the Role Experteer Overview In this role you drive DL-based surrogate modelling and generative AI within Siemens PhysicsAI, translating research into production-ready solutions for industrial design problems. You work within a collaborative team focused on 3D genAI and geometric deep learning to accelerate product design. You tackle challenging engineering problems, assess new AI methods, and deliver production-grade code that integrates into Simcenter PhysicsAI. This is an opportunity to shape AI methods for engineering simulation at scale. Pay / Benefits * Identify and explore emerging deep learning techniques for mechanical, aerospace, and civil engineering problems * Advance promising approaches to production-ready implementations * Evaluate current genAI capabilities to guide future method development * Gather and translate customer needs by collaborating with application engineers and specialists Tasks * Master's or PhD in a technical field (e.g., Computer Science, Engineering, AI, aaaa Overview Physics) * Strong theoretical grounding in deep learning fundamentals * Familiarity with transformers, diffusion models, normalizing flows, and Graph Neural Networks * Knowledge of physics-based simulation (FEA, CFD) and PDEs with numerical methods * Experience with mesh-based processing and major DL frameworks (PyTorch or TensorFlow) * Experience working on large, complex code bases * Strong problem-solving and clear communication of technical results Key requirements * hybrid by default * health and wellness benefits * incentive compensation * global mobility * merit-based career growth * diversity & inclusion initiatives ## Description Experteer Overview In this role you drive DL-based surrogate modelling and generative AI within Siemens PhysicsAI, translating research into production-ready solutions for industrial design problems. You work within a collaborative team focused on 3D genAI and geometric deep learning to accelerate product design. You tackle challenging engineering problems, assess new AI methods, and deliver production-grade code that integrates into Simcenter PhysicsAI. This is an opportunity to shape AI methods for engineering simulation at scale. Pay / Benefits * Identify and explore emerging deep learning techniques for mechanical, aerospace, and civil engineering problems * Advance promising approaches to production-ready implementations * Evaluate current genAI capabilities to guide future method development * Gather and translate customer needs by collaborating with application engineers and specialists Tasks * Master's or PhD in a technical field (e.g., Computer Science, Engineering, AI, Mathematics, Physics) * Strong theoretical grounding in deep learning fundamentals * Familiarity with transformers, diffusion models, normalizing flows, and Graph Neural Networks * Knowledge of physics-based simulation (FEA, CFD) and PDEs with numerical methods * Experience with mesh-based processing and major DL frameworks (PyTorch or TensorFlow) * Experience working on large, complex code bases * Strong problem-solving and clear communication of technical results Key requirements * hybrid by default * health and wellness benefits * incentive compensation * global mobility * merit-based career growth * diversity & inclusion initiatives ## Related Videos - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [30 Golden Rules of Deep Learning Performance](https://www.wearedevelopers.com/videos/11-30-golden-rules-of-deep-learning-performance) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)