Postdoctoral Fellow in Atomistic Simulations and AI for Materials Design

Postdoctoral Fellow in Atomistic Simulations and AI for Materials Design Johns Hopkins University Maryland Not specified About This Opportunity Johns Hopkins University is recruiting a Postdoctoral Fellow in atomistic simulations and AI for materials design. The role focuses on DFT, machine-learned force fields, graph neural networks and large language models for materials discovery. The AtomGPTLab at Johns Hopkins University is recruiting a postdoctoral fellow in atomistic simulations, machine-learned force fields and artificial intelligence. The researcher will help build a computational platform that integrates first-principles methods, molecular simulations, graph neural networks and large language models to accelerate experimental design and discovery of functional materials. The role includes high-throughput DFT, model development, data integration, open-source contributions, mentoring and manuscript preparation. Atomistic Simulation and AI for Materials Design Materials Science Level Postdoc Field Atomistic Simulation and AI for Materials Design Organization Type University Funding & Compensation Amount Paid Funding Type Salary Funding Status Paid Requirements Education Applicants must hold a Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Computer Science or a related field. Experience Applicants must demonstrate experience in at least one of density functional theory, machine-learned force fields, graph neural networks or large language models. Technical Skills Density functional theory Machine-learned force fields Graph neural networks Large language models VASP Quantum ESPRESSO GPAW

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HuggingFace OpenAI AtomGPT JARVIS-Tools ASE High-performance computing Python Git Conda packaging Surrogate modeling General Skills Interdisciplinary collaboration Mentoring Manuscript writing Grant proposal contribution Scientific communication #J-18808-Ljbffr Laplace Expert Ltd