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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI
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State University and work closely with I-CREWS researchers across the state. The position emphasizes developing, integrating, and applying modeling approaches-including machine learning (ML), hydrologic
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. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program. This program
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direct services, such as health care. Connections working at Washington University in St. Louis More Jobs from This Employer https://main.hercjobs.org/jobs/21931976/postdoctoral-research-associate
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Successful applicants will have: PhD and postdoctoral fellow training with expertise in cancer biology, proteomics and/or computational biology / machine learning A proven track record with first author
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software related to the medical field Experience of specific software and programming languages, specifically ones suitable for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 27 days ago
hyperscanning neuroimaging data, using advanced statistics and machine learning methodologies for temporally-sensitive data, such as GLMM, Random Forests, LSTM, etc.. Use of MatLab for pre-processing, and
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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resilient future. The Postdoctoral Associate will have the opportunity to align with the most relevant academic department in the College of Architecture, Art, and Planning and teach one course per year
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an integrated framework to explore advanced workloads including simulations with in-situ visualization and, possibly, machine learning integration. This work will inform future ALCF platform procurement decisions