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Computer Engineering. Expertise in computer vision algorithms and image processing techniques (such as object detection, segmentation, and feature extraction). Proficiency in deep learning frameworks such as
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computer vision, NLP, and other AI domains to biological problems Build computational frameworks that integrate multi-scale immune data for digital twin development Implement rigorous model validation
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, Massachusetts 02215, United States of America [map ] Subject Area: Computer Engineering / machine learning and other related areas Appl Deadline: none (posted 2026/01/30 05:00 AM UnitedKingdomTime) Position
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related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with transformer architectures (e.g., ViT
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intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in
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of Machine Learning, Computer Vision, Large Language Models and related technologies. Relevant publications – articles in peer-reviewed scientific journals indexed in WOS with an impact factor. Excellent
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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 9 days ago
machine learning applied to natural language processing, computer vision, or a related area. Strong publication record in NLP, ML, or related areas -Strong programming skills, including TensorFlow and/or
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high-quality research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition
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applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata. Build and evaluate monocular depth pipelines