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Field
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, the Associate will assist with research and development projects in the areas of robotics, machine learning, control systems, and/or computer vision. They will be responsible for: designing and analyzing
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robotics, and human-machine interfaces. We are looking for an ambitious researcher who is looking to use this opportunity to grow towards the next level of research. The position is renewable each year based
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., transcriptomics, proteomics, metabolomics) and artificial intelligence/machine learning (AI/ML) applications in biomedical research will be considered a strong advantage. Outstanding UA benefits include health
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Intelligence (AI) and Machine Learning (ML) methods to tackle complex biomedical challenges in nutrition and health. This is a one-year full-time benefits-eligible position that may be extended for up to four
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, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being. Learn about NREL’s
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Acquire, process, integrate, and standardize large-scale multi-omics datasets and build databases Perform integrative and exploratory analyses of multi-omics datasets and apply machine learning methods
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) at the University of Florida (UF) is seeking a highly motivated and ambitious Postdoctoral Researcher with a strong background in Artificial Intelligence and Machine Learning (AI/ML). This is an exciting opportunity
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learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology, genomics, and epigenetics. Experience in next-generation sequencing data and scRNA-seq data
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. Research Themes and Projects: We are an interdisciplinary research team integrating single-cell and spatial genomics, lineage tracing, synaptic proteomics, functional perturbation screening, and machine
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning