75 structures-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"CEA-Saclay" Fellowship positions in United States
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will work with Dr. Baladandayuthapani and his research group in developing statistical and computational methods for large-scale, high-dimensional, complex-structured biomedical data. The research topics
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The Postdoctoral Fellow will: Collaborate with the PI and interdisciplinary team on conceptual development, data construction, analysis, and writing. Contribute to the design and implementation of quantitative text
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protected by law. Pay Transparency Statement The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and
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areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
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to the field Proven ability to solve challenging technical problems Clarity of thought in written and oral communication skills Pay Transparency Statement The hiring range is based on market pay structures, with
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transcriptomics datasets generated by the host laboratory. To develop insecticidal molecules, the Fellow will utilize AI/machine learning, structural and computational biology, bioinformatics, and genomics tools
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member who serves as a mentor for the postdoctoral appointee. Additional Department Summary: The Civil, Construction, and Environmental Engineering Department at The University of Alabama is seeking
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participation in research meetings and other activities associated with being affiliated with a medical device research laboratory including: 1) Design, modeling, construction, documentation and testing of state
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structure and reactions, and in fundamental symmetries. The group leads experimental research programs at various particle accelerator laboratories, focusing on unstable beam experiments at the nearby
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documents into appropriate structures for efficient training, establishing evaluation metrics to validate model performance, and improving the fine-tuning process with additional reinforcement learning steps