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evaluate innovative methods based on generative models and Vision-Language Models. Design, implement, and validate deep learning approaches for vision applications. Publish research results in leading
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, a novel spatial discovery proteomics concept that integrates microscopic cell phenotyping with deep-learning based image analysis and global MS-based proteomics. This unique method was recently
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neuroscience, and brain-computer interfaces, machine learning and deep learning, statistical modelling, regression methods, and uncertainty quantification, calibration, interlaboratory comparisons, and
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discipline Strong experience in integrating several of the following components: Deep learning and LLMs for molecular biology Vision foundation models for pathological image analysis Multi-omics datasets (e.g
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
Posting Information Posting Details Department Globl Hlth and Infect Disease - 427801 Posting Open Date 04/10/2026 Application Deadline 04/24/2026 Open Until Filled No Position Type Postdoctoral
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
Posting Information Posting Details Department Globl Hlth and Infect Disease - 427801 Posting Open Date 04/10/2026 Application Deadline 04/24/2026 Open Until Filled No Position Type Postdoctoral
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foundation in machine learning, deep learning, or computer vision Proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow Demonstrated research productivity (e.g., peer-reviewed
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to address "grand challenge" style problems in line with their research vision together with their faculty host. Postdoctoral positions supported by CBI provide remarkable opportunities to shape the next
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required Demonstrated expertise with large language models (fine-tuning, prompting, deployment) Strong Python programming with deep learning frameworks (PyTorch, TensorFlow) Experience with unstructured
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving