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Field
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Staff Union Non-Union Non-Classified Staff Pay Grade Level Grade Level: 99 Pay Grade Range N/A Status Calendar Year, Full-time, Limited Department Information Department Elec, Computer & Bio Engr
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About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine
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experience in blockchain technology (preferably Ethereum) and/or machine learning. Solid foundation in computer network and/or data analysis. Strong programming skills, preferably in Java. Ability to work
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brain network discovery and individualized circuit targeting, multimodal concurrent brain stimulation-recording, and computational modeling. We bridge invasive approaches, including intracranial
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include semantic and context-aware networking, resource management in edge computing systems, and AI-native network control. An important part of the role is designing and building realistic simulators
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treatment optimization • Biomedical knowledge graphs and network medicine • Translational data science for therapeutic discovery Primary Responsibilities: The Postdoctoral Research Associate is expected to
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- Provisional Positions Department's Website: https://cosmos.ualr.edu/ Summary of Job Duties: The Postdoctoral Fellow position is a full-time, provisional position with the COSMOS Research Center
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- Provisional Positions Department's Website: https://cosmos.ualr.edu/ Summary of Job Duties: The Postdoctoral Fellow position is a full-time, provisional position with the COSMOS Research Center
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Max Planck Institute of Molecular Cell Biology and Genetics | Dresden, Sachsen | Germany | about 2 hours ago
Applied Algebraic Geometry * Computer Algebra * Data Science / Mathematics of Data * Dynamical Systems and Differential Equations * Information Geometry * Higher Structures and Category Theory * Fluid
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Prior involvement in clinical trials or clinical research with stroke or aphasia populations Experience with network neuroscience or connectivity analyses Familiarity with brain-computer interface