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: investigating the neural mechanisms regulating reward for social interactions in a laboratory rodent model. Responsibilities will include but are not limited to: Performing research experiments (e.g. social
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Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) | Leipzig, Sachsen | Germany | 3 months ago
networks, and computational modelling. Within the Department, we maintain strong synergies with the Neural Computation Group (PI: Andrej Bicanski ), which develops mechanistic computational models of brain
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the names and contact information of three professional references. 7. Ability to model Argonne’s core values: Impact, Safety, Respect, Integrity, and Teamwork. 8. Ability to work onsite at Argonne
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characterization using advanced analytical tools, such as synchrotron, neutron, and laboratory equipment. Experience in data analytics and modeling tools. Special Requirements: Applicants cannot have received
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cellular neuroscience/stem cell lab for disease modeling using patient-derived induced pluripotent stem cells (iPSC). The ideal candidate will have experience in cell culture, rodents, biochemical, molecular
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science. The postdoc will work on a variety of projects, which may include methods for large language models, the impact of artificial intelligence on society, as well as broader questions surrounding
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. In complementary studies, we are investigating antigen-specific responses and mucosal tolerance using multiple different in vivo and in vitro models and human samples. Candidates with backgrounds in
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mainly be connected to DRIVE PR, but may also be linked to related projects within data-driven product realisation, digital engineering, systems engineering, geometry assurance, automation, or model-based
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
new immune-epithelial-mesenchymal co-culture models; perturbation approaches to define region-specific transcriptional regulation of epithelial homeostasis; characterization of sputum and mucus
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, improving faculty pre- and post-award service, strengthening compliance support, generating better research intelligence, and creating a scalable model for responsible AI use in research administration