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Field
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. The successful candidate will contribute to understanding how modern machine learning models represent information internally and how their predictions can be made transparent, reliable, and clinically meaningful
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 10 hours ago
science, or a related field; experience with using and building machine learning models, developing and validating computational analysis workflows, and developing circuit models is preferred; excellent
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 9 hours ago
) Optimization and parameter identification methods Data-driven modeling and machine learning Physics-Informed Learning (or hybrid modeling approaches) Handling and analysis of large-scale datasets (e.g., mobility
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 11 days ago
of meteorites as well as numerical modeling on state-of-the-art supercomputers. We invite applications for a Postdoctoral Position (m/f/d) in machine learning for PDEs and turbulence control. Machine learning
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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) Experience in genomics, single-cell data, or machine learning (preferred) Why this is exceptional Build next-generation AI models of the human genome Work with one of the richest longitudinal PD datasets
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issues. Proficiency in urban modeling tools such as MATLAB, Python (especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning
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modeling, satellite remote sensing, or machine learning Programming skills (Python or R) Strong publication record
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track record in neurobiologically mechanistic modeling (i.e., models should incorporate known neurobiology and neurophysiology, rather than relying on black-box machine learning approaches