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Position Description The School of Physics (https://physics.gatech.edu/ ) at the Georgia Institute of Technology in Atlanta, Georgia invites applications for a Postdoctoral Fellow position in Artificial
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
retrieval algorithm development with focus on using the polarimetric signals, the new FIR or sub-mm bands, and/or the ML/AI approach; (3) ML/AI application on system/pattern tracking on satellite images
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, evaluate and describe novel algorithms for learning concepts with theoretical guarantees from unstructured data; present research results at international conferences, workshops, and journals; pursue and
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the project activities. – Assist in the dissemination of project results through presentations, publications, and stakeholder engagement. Development of algorithms (80%) – Conduct a comprehensive review of the
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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: genetics, epigenetics, inflammation, metabolic pathology, autoinflammatory pathology, autoimmunity, arthritis, computational analysis, mathematical modeling, applied algorithms, machine learning in biology
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, manuscript preparation, meeting with collaborators, etc. In particular, the Research Scientist hired for this position is expected to develop AI algorithms for the directed evolution of proteins with a
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new AI algorithms for science. Our group also welcomes new research directions, and collaboration across different groups at the laboratory and beyond. We publish in peer-reviewed journals and
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applicant will work with the ReXIl team, AIML, and 4DMedical to turn data into clinical impact. They will be responsible for developing algorithms for image analysis, creating predictive models for disease
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using LLMs in therapeutic settings: data confidentiality, algorithmic biases, and limitations in contextual understanding. Study the acceptance of these tools by both patients and healthcare professionals