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Field
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related dementias. Project Overview Leveraging newly developed brain organoid models, this project will: Utilize human iPSC lines from AD patients to develop multiple tiered brain organoid models
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 277494287 Position: Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in
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Medical Center. Dr. Salehi's lab is at the forefront of research in brain cancer therapeutics. Our work focuses on developing and validating preclinical models for the treatment of neuro-oncological
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and capacity evaluations for CO₂ sequestration. This position includes a health, dental and vision insurance program . Responsibilities and Essential Duties • Conduct reservoir simulation modeling
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Job Description Job Responsibilities: -Design and implement AI/ML models to analyze large-scale agricultural datasets (e.g., field trials, satellite imagery, IoT sensor data). -Develop pipelines
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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disease with a focus on Alzheimer’s Disease. Computational models will be developed that utilize data obtained from a wide range of experiments, from basic biochemical methods to advanced imaging techniques
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Classification Title: Post Doc Associate Classification Minimum Requirements: Ph.D. degree in biomedical informatics/bioinformatics, computer science, data science, electronic/biomedical engineering
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modeling. Positions may begin as soon as September 2025 . A Ph.D. in Mechanical and Aerospace Engineering, Civil and Environmental Engineering, Atmospheric and Oceanic Sciences, Geosciences, Computational
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
computational methods. These quantities feed into our group's thermodynamic and geophysical numerical models. In addition, we are interested in investigating the consequences of the presence of organic matter in