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vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is preferred. Apply online at https
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website: https://cruchagalab.wustl.edu/ . Research Projects: Plasma, CSF and Brain Proteomic analysis. Biomarker identification through the use of machine learning and AI approaches. Integration
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broader university. The Postdoctoral Research Associate will be responsible for conducting field, laboratory, and/or computer modeling studies to address research questions in the Geological and/or
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
Posting Information Posting Information Department Psychiatry - Research - 412250 Posting Open Date 01/21/2026 Application Deadline Open Until Filled Yes Position Type Permanent Faculty Working
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Research Centre. Mōu | Who You Are To be successful in this position, ideally you will have: A PhD in Computer Science or a closely related field Expert knowledge of deep learning, large language models
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experience with managing, processing, and analyzing large datasets and strong programming skills especially in Python. ● Experience working with transmission power flow and machine learning models. ● Strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
the development and implementation of machine learning models Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https
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Hamburg, ESRF in Grenoble and others) analysis of the experimental data, ideally connecting to our machine learning tools presentation of scientific results on conferences and in publications supervision