724 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof"-"Prof" Fellowship positions in United States
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to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross
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learning, and data science, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 13 hours ago
software tools in order to develop biometric algorithms for recognition, spoof detection, fairness in AI, template security, and explainability, and related research areas, as well as paper and report
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
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objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms (50%). PhD in computer science, engineering
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science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood biomarkers, and
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human disease, and developing and applying new computational algorithms to decipher it Enjoy working closely and collaboratively to solve complex biological problems Able to lucidly present complex
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, findings, data, software, etc. are correctly archived and transmitted through appropriate channels. Key responsibilities will include but are not limited to: Algorithm development, implementation, and
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research initiatives that analyze the impact of AI technologies on social systems and design innovative methods for adapting economic and social governance to AI development. A special focus will be
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designs and methods, clinical trial methods, Bayesian methods, and developing R packages and scalable algorithms. Opportunities for collaboration across the Department of Biostatistics and the Medical