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savings options Employee and dependent educational benefits (when applicable) Life insurance coverage Employee discount programs Posting Summary This position supports advanced experimental research in
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/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g., concept bottlenecks, prototype
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, molecular and large omics data studies. In addition to experimental research and contributions to maintaining the laboratory, the Postdoctoral Associate will be expected to prepare manuscripts for publication
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of the cellular localization of B. thetaiotaomicron HTCS proteins. The research will involve both cellular and in vitro studies. In addition to experimental research and contributions to maintaining the laboratory
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to transition to the next phase of their career, the applicant(s) will be trained in improving their experimental design skills and their oral and written presentation skills. Multiple resources for career
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required. Must have experience with and/or working knowledge of multiple experimental techniques, including one or more of the following techniques: PCR, RT-qPCR, ELISA, RNAseq, isolation of extracellular
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Qualifications Minimum Education and Experience Ph.D. in Neuroscience, Cognitive Neuroscience, Neurobiology, or related field. Rigorous training and experience in statistics, data analysis, and human experimental
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would include using a diversity of organisms in experimental systems to explore how rapid evolution influences interspecific interactions in multispecies systems. Position Status Full Time Posting Number
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related science field required. Must have experience with and/or working knowledge of multiple experimental techniques, including one or more of the following techniques: PCR, RT-qPCR, ELISA, RNAseq
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transformer architectures (e.g., ViT/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g