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, or climate data is advantageous but not required. What We Offer A vibrant interdisciplinary environment integrating machine learning and sustainability science. Access to high-performance computing resources
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
management. Develop and validate computational models for monitoring and predicting infrastructure performance. Collaborate with faculty and researchers across SHORES. Disseminate research findings through
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Materials science and technology are our passion. With our cutting
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8 Dec 2025 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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regulation, or aging biology Interest in applying AI to biological systems and contributing to data-driven hypothesis generation Experience with Linux-based computational environments or high-performance
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Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
performance. Collaborate with faculty and researchers across SHORES. Disseminate research findings through high-impact publications and conference presentations. Mentor graduate and undergraduate students
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provides excellent research computing resources (high-performance computing clusters, large-scale storage, and advanced visualization). Initial term: 2 years, renewable for a 3rd year contingent on
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-Informed Neural Networks (PINNs) and geometric deep learning. Experience with active learning, agentic workflows, or other methods for autonomous experimentation. Familiarity with high-performance computing
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Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing