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, Data Science, Machine Learning, or a related field. Experience and skills · Strong knowledge of AI, Machine Learning, data-science (e.g., neural networks, deep learning, autoencoders, GANs, active
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the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create interpretable, data-driven observers that enable physically grounded perception and control for robust
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should possess a PhD in Computer Science or related area. We are looking for candidates who have publications in top conferences like NeurIPS, ICML, ICLR, CVPR, etc. A strong background in deep learning
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optimal transport and gradient flows to machine learning and optimization applications, such as deep generative models, sampling, inference, stochastic optimization, and beyond. The doctoral student will
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for a candidate with: an MSc in computer science, artificial intelligence or a related field a creative and collaborative mindset strong programming skills in Python or Rust strong skills in deep learning
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) faculty are committed to enhancing student success by engaging students in quality academic instruction, research, internships, global studies, and other experiential learning opportunities. There is an
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) faculty are committed to enhancing student success by engaging students in quality academic instruction, research, internships, global studies, and other experiential learning opportunities. There is an
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AHPRA as Registered Nurse with no condition Post graduate nursing qualifications: Graduate certificate minimum. PhD or Masters level desirable. Experience in university-level learning and teaching
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connection with the legal adoption of an eligible child, such as travel or court fees, for up to two adoptions in your household. To learn more, please visit: https://www.hr.upenn.edu/PennHR/benefits-pay
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experience in NGS data analysis and genomics pipelines since similar to proteomic pipelines. Record of prior first-author publications. A deep interest in biomarker research and discovery. The drive to pursue