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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 27-Jan-26 Location: New York, New York Categories: Academic/Faculty Internal Number: 179125 Postdoctoral Researcher
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monitoring. Familiarity with computational image analysis, scripting (Python, MATLAB), or machine learning–based image workflows. Experience with method development, imaging assay optimization, or pipeline
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microscopy methods (darkfield, photothermal, ultrafast, interferometric), electron microscopy, machine learning and other advanced statistical methods. Required Application Materials Cover letter, curriculum
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, embracing failure as a learning opportunity, and continuously enhancing our knowledge and methods to tackle local, national, and global challenges. The postdoctoral associate will work directly with both
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, geolocation and AI-enabled communication and networking systems. In these roles you will undertake research centered on the intersection of networking, communications, geospatial methods and machine learning
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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turbines represented using an actuator-line approach, assess the applicability and limitations of reduced-order models in predicting turbine performance, and develop machine-learning surrogate models capable
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close collaboration with a specific group (DARSA) specialized in developing and applying remote-sensing tools and innovative open-source machine-learning methods. Key responsibilities Develop effective
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language processing, machine learning and skills taxonomies, you will help generate meaningful insights into current and future engineering skills needs. Your work will support industry, policymakers, educators and
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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance