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coarse-grained models that can be analyzed and simulated. Strong applicants with backgrounds in applied and computational mathematics, biophysics, engineering, statistical inference, and related fields
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image processing (e.g., in Matlab), and Fourier optics are desirable. Knowledge of visual optics is not required, though beneficial. The project is supported by federal funding. Rank and salary will be
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, including gene therapy and imaging technologies. Central to our studies is the lethal pediatric brain tumor, Diffuse Intrinsic Pontine Glioma (DIPG), particularly targeting cancer stem cells to address
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landscape design to influence global climate-system dynamics. Martin Bechthold, Material Processes and Systems (MaP+S) Group: The MaP+S Group advances knowledge about design materials through a combination of
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related to the upper human airway. The successful candidate will contribute to cutting-edge research projects involving computational models, medical image data processing, and developing idealized and
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Experience with high performance computer clusters (e.g, TAMU-HPRC, UT-TACC, NVIDIA Data Center). Preferred Qualifications Background in estuarine ecology, aquatic vegetation Experience with image analysis
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for research staff positions at the Lab after their fellowship appointments are complete. The recipients – up to two for this round of the selection process – must have a strong desire for independent research
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reconstruction, processing, synthesis, and registration, as well as AI for treatment outcome prediction and clinical decision making. The projects will involve using multi-modality images (CT, CBCT, MRI, PET
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models and other natural language processing techniques applied to language understanding and the next generation of search engines. AI + Health: This area levarages AI to study and solve complex problems
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degree in computer science, information technology, engineering, health informatics or a related field; Research expertise and strong background in one or more of the following areas: Computer programming