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spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025, and will remain open until excellent fits are found.The
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targets. You will take a lead on development of computational approaches to integrate multi-omics data from patient samples, including DNA methylation, histone modifications, single-cell transcriptomics and
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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includes large-scale precipitation and temperature manipulation in combination with reciprocal transplants of genotypes of common tansy (Tanacetum vulgare) and paper birch (Betula papyrifera) across four
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, epidemiology, biostatistics, genomics, big data analytics, or artificial intelligence analytics Be familiar with conducting analysis with different types of data, including metagenomics sequencing, genomics
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of Public and International Affairs. The research position requires a PhD in a relevant field (e.g., geography, urban planning, data science, sociology, public health, emergency management). Ideal
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The Princeton University WET LAB (https://ren.princeton.edu/) is seeking a postdoctoral research associate(s) or more senior researcher(s) with expertise and interest in Large Language Models (LLM
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limited observational data. WaterColor seeks to fill these critical knowledge gaps through an integrated approach that combines field observations, satellite remote sensing, and advanced optical techniques
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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
, or translational breast cancer research. The successful candidate will lead research efforts using rich molecular and epidemiologic data from the Carolina Breast Cancer Study (CBCS), a large, diverse population