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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
to the development and validation of computational methods that integrate images with other multimodal data. The postdoctoral research associate will design, implement, and evaluate algorithms and models
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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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into broader health informatics systems. Provides expert annotations for training large language models (LLMs) and NLP algorithms, focusing on healthcare-specific use cases. Presents findings in department
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Starting Date 1 Jan 2027 Is the job funded through the EU Research Framework Programme? Horizon Europe Is the Job related to staff position within a Research Infrastructure? No Offer Description As part of
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a sequential decision-making process explored through computational simulation and deep multi-objective reinforcement learning. The project will investigate a simulation platform that reproduces
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into broader health informatics systems. Provides expert annotations for training large language models (LLMs) and NLP algorithms, focusing on healthcare-specific use cases. Presents findings in department
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: Integrated sensing and communication Cell-free massive MIMO beamforming, and MIMO algorithms Joint optimization of communication and computing resources Preferred qualifications A doctoral degree or an
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efficient transmission and robust communication. This work involves formulating rigorous analytical models, designing efficient algorithms, and establishing performance characterization methods that drive
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project of the VUB, introduces a new research framework that treats archaeological prospection as a sequential decision-making process explored through computational simulation and deep multi-objective
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics