Postdoctoral Researcher (Academic Research Assistant) – Foundation Models and Agentic AI for Physical Systems

Descrizione

Postdoctoral Researcher (Academic Research Assistant) – Foundation Models and Agentic AI for Physical Systems Sintesi in italiano (traduzione automatica): La Chair di Simulazione e Analisi Basata sui Dati in Scienza dei Materiali presso l'Università di Saarland, in collaborazione con il Centro di Ricerca Tedesco per l'Intelligenza Artificiale (DFKI), cerca un ricercatore post-dottorato. Il candidato selezionato contribuirà a ricerche innovative nell'ambito dell'intelligenza artificiale, della scienza computazionale e dell'ingegneria, sviluppando modelli fondamentali e sistemi di AI agentici. Le principali mansioni includono la conduzione di ricerche indipendenti, lo sviluppo di progetti innovativi, l'integrazione di metodi AI con simulazioni numeriche e la pubblicazione dei risultati in conferenze e riviste di prestigio. È richiesta una laurea in un campo pertinente, come ingegneria o scienze computazionali, e competenze in machine learning e simulazione scientifica. The newly established Chair of Data-Driven Simulation and Analysis in Materials Science (Prof. Dr. Roland Aydin) at Saarland University, jointly affiliated with the German Research Center for Artificial Intelligence (DFKI), invites applications for a postdoctoral research position. The group develops foundation models, large language models (LLMs), and agentic AI systems for scientific discovery, engineering, and physical systems. The successful candidate will contribute to cutting-edge research at the intersection of artificial intelligence, computational science, and engineering. Current Research Directions AI for Scientific Computing Neural Operators and Learning-Based Surrogates LLMs and Scientific Agents Agentic AI for Engineering Design Multimodal Scientific AI Alignment and Verification of Scientific AI Systems AI for Materials Discovery Generative Models and Active Learning for Scientific Applications Responsibilities The successful candidate will: Conduct independent postdoctoral research and establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific computing and numerical simulation workflows. Publish in leading conferences and journals (e.g. NeurIPS, ICML, ICLR, AAAI, npj Computational Materials). Present research results at international conferences. Collaborate with partners at EPFL and Hamburg University of Technology. Contribute to the preparation of research proposals and future funding initiatives. Supervise PhD, Master’s and Bachelor’s students. Support teaching activities and interdisciplinary collaborations. Annuncio in inglese. Fonte: Euraxess (Commissione europea).