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Mathematical Sciences at The University of Texas at El Paso (UTEP) is seeking data scientists with expertise in Big Data Analytics/Machine Learning/Artificial Intelligence/Statistical Modeling and/or High
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and clinical datasets Statistical modeling and survival analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional
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and clinical datasets Statistical modeling and survival analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional
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, or machine learning approaches for handling big data in order to improve scientific insight and actionable information derived from NASA datasets. Candidates interested in leveraging multi-mission
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reconstruction), machine learning (including big data analytics and adversarial machine learning), natural language processing (audio-visual multimodal understanding), autonomous systems (such as driverless cars
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to develop a biophysically interpretable machine learning model that integrates diverse biological data—including transcription factor (TF)–DNA interactions, epigenetic features, and three-dimensional
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Helmholtz Association of German Research Centres | Kiel, Schleswig-Holstein | Germany | about 1 month ago
jobs PhD in Trustworthy World Models for Critical Systems Luxembourg, Luxembourg (Canton) Professor of Machine Learning Methods 2 Graz (AT) Faculty Position - Department of Epidemiology and Cancer Control, Data Science Memphis, Tennessee
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. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
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. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
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of small-molecule drugs, nanomaterials/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning