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Field
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Classification Title: Post Doctoral Associate Job Description: A Post-doctoral Associate in Social Network Analysis position is available for up to 2 years to work within the NSF supported project
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and compare two distinct mathematical approaches to network metrology: Spectral analysis approach – based on network layer decomposition and spectral measures on singular values to mathematically
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emphasize the different kind or levels, known as layers, of connections between the elements of the network and the interactions between these levels as well. In order to capture the structure and complexity
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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of modeling higher-order relational structures such as hypergraphs and simplicial complexes, which are prevalent in complex biological systems like protein assemblies, signaling pathways, and metabolic networks
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the following topics: Large Language Models and Multimodal Language Models Generative Networks and Diffusion Models Program Analysis Software Testing Automation The candidate should have critical thinking and
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or demonstrated interest in entrepreneurship, small business management, strategic decision-making, supply chain management, and\or network analysis. Ability to acquire and work with existing data sources
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, quantitative and qualitative data analysis; and working with a network of European collaborators (the EuroWISE collective). Work Package 2 (Analysis and Data Management): The PDRA will be responsible for data
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-established data resources accessed within a secure Trusted Research Environment for large-scale analysis. This role offers excellent opportunities to engage with a broad network of collaborators including
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and analyzing global field datasets from contrasting timber production systems in order to identify which landscape-level combinations of systems best balance biodiversity, carbon, and yield outcomes