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observational data of non-CO2 greenhouse and ozone-depleting gases (e.g., N2 O, CFCs, HFCs), and to extract diagnostic insights from instrument performance indicators, using machine learning methods. Additional
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About the Opportunity Job Summary: The Lopez Group at Northeastern University is seeking a postdoctoral researcher with experience in machine learning and organic chemistry to join a collaborative
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analysis, machine learning, mathematics of data scienceMathematical modeling and manifold learning of high-dimensional data geometry, with theoretical foundations and applications in evolutionary biology and
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an established code (for example VASP, Quantum ESPRESSO). ● Research experience performing molecular dynamics simulations. ● Experience training, fine-tuning, or validating machine-learning interatomic
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transformation, machine learning, and data analysis applied in logistics and supply chain management; support graduate-level teaching activities for both the Supply Chain Management residential (SCMr) and Supply
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and growing community. Learn more here: https://research.duke.edu/prospective-postdocs/. Screening of Applications Screening continues until position is filled. Job Code: 00003820 POSTDOCTORAL ASSOCIATE
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multimodal data analysis is preferred; experience with R, machine learning, or advanced statistics is a plus. Training and Research Environment: The successful candidate will receive interdisciplinary training
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machine learning, topological quantum materials, and/or related areas. The successful candidate will have access to HiPerGator, the fastest university-owned supercomputer in the United States (TOP500
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to develop fundamental theory and methods that enable machine learning systems to be deployed in a trustworthy manner. The project spans human-AI interaction, fairness, transparency, privacy and other
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its treatment options in patients with OSA. Newly NIH funded projects also include mathematical modeling and machine learning of models of tissue hypoxia using sleep studies and molecular markers