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techniques Background in biomineralization or structural biology, or desire to work within research that has a marine environmental sustainability perspective Previous work with deep learning frameworks (e.g
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Cultural Studies, History, or related field Demonstrated expertise with large language models (fine-tuning, prompting, deployment) Strong Python programming with deep learning frameworks (PyTorch, TensorFlow
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, machine/deep learning, bioinformatics methods in -omics data are preferred. Demonstrated evidence of excellent programming, collaboration, and communication skills. Responsibilities: As a Postdoctoral
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Episteme, Condensed Matter Theory Group Position ID: Episteme-Condensed Matter Theory Group-POSTDOC [#31188] Position Title: Position Type: Postdoctoral Position Location: Cambridge, Massachusetts
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acquire research training. In addition to career development, the postdoctoral scholar and PI will create and follow mentoring and individual development plans. Minimum Requirements Minimum qualifications
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postdoctoral or more senior researcher interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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. Candidates whose doctoral work focused on deep learning methods and who have a strong interest in genomics will also be considered. Experience: At least one publication in computational genomics or machine
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across Africa using satellite remote sensing, atmospheric modeling, and deep learning. Research Focus Estimate cropland emissions (NH3 , N2 O, CO2 , CH4 ) using satellite observations, atmospheric
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foundation model methodologies, with federated learning serving as a key enabling research direction. The postdoctoral researcher will be advised by the principal investigator, while being expected to exercise