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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
climate policy, GHG accounting, or net-zero emissions planning. - Familiarity with data-model integration techniques and scenario analysis. - Well-developed critical and analytical skills. - Excellent
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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As a flagship research center in nanoscience and nanotechnology, our mission is to open and explore new frontiers of knowledge at the nanoscale, and bring value to society in the form of new
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) Development of an Augmented Smart Classroom for Personalized Learning (SmartClass) serving as a test-bed for the collection and analysis of students and professors data, leveraging on data analytics and machine
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, evolutionary theory, quantitative genetics, data science, toxicology, and law. Within this project, our group at the CRG focuses on the analysis of bulk and single cell RNA-seq from five different model species
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of biological brains. Spiking neural networks (SNNs) can offer increased processing speed and reduced power consumption, especially when implemented on dedicated hardware (neuromorphic chips or FPGAs). Standard
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analysis, work with large language models, network analysis, causal inference in machine learning and agent-based modelling. Experience in collecting, curating and analyzing large digital datasets with
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focused on understanding and countering harmful narratives and, mis/disinformation, and applying social network analysis. To be successful you will need: PhD in a relevant discipline such as computer
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., omics or clinical data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, with a focus on omics data
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the research team around Univ.-Prof. Dr. Philipp Grohs. Our ideal candidate has a strong interest in Applied Mathematics, possesses solid and profound background knowledge in Numerical Analysis, Approximation