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Assistant Professor/Associate Professor/Professor (Open Rank), School of Law – Health Policy and Law
law; as well as a deep understanding of law and policy as it relates to Medicare, Medicaid, the Affordable Care Act, universal health insurance; and public health challenges and societal health risks
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Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 days ago
access control, discovery, preprocessing, analytics, deep learning and . Fed-BioMed is currently involved in EU Horizon and ANR projects. 1) TwinRISE is a Horizon Europe project building AI-powered digital
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, extract, and standardise functional information 2. Develop computational tools that integrate evolutionary and functional information using comparative genomics and deep learning approaches 3. Apply
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an ambitious, leading faculty in education and high-quality research, characterized by a strong international orientation and deep roots in the Northern Netherlands. We create and share knowledge through
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insurance, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records
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need to match every topic or method listed below. We value deep expertise in at least one area, intellectual range, scientific ambition, and the ability to collaborate across computer science and the
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on machine learning and networks, release the code in open access and actively participate in the international interpretability community. Where to apply Website https://seuelectronica.upc.edu/en/procedures
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LevelMaster Degree or equivalent Skills/Qualifications Solid background in Machine Learning and Deep Learning. Experience or interest in agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen, or similar
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with deep generative models (VAEs, GANs, diffusion models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as
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. Preferred Qualifications Strong computational and data analysis skills with experience developing analytical methods. Experience with machine learning, deep learning, graph-based models, variational