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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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the evaluation of converter and drive architectures for edge-resident intelligence; the development of advanced modulation, estimation and control algorithms for high-performance operation; and the integration
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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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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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, 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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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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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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, 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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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