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Sciences | Psychology The Center for Cognitive and Behavioral Brain Imaging (CCBBI) invites applications for a Post Doctoral Scholar position that will be based in the Department of Psychology. CCBBI is a
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on the development and validation of a new humanized computational model of cochlear nerve responses to electrical stimulation under the mentorship of Dr. Ian Bruce. This work will integrate experimental data obtained
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conduct assigned research projects involving human tissue and fluid samples as well as mouse models. Responsibilities include animal tissue harvest and processing, flow cytometry and FACS sorting, neuronal
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translational research approach that integrates human iPSC-based models, in vivo disease models, advanced Ca²⁺ imaging, confocal microscopy, molecular cloning, gene editing, behavioral phenotyping, functional
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modeling, and high-field NMR spectroscopy. The research will focus on the structural and dynamics of characterization of peptides, peptide analogs, and related molecules, and their interactions with specific
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biochemical or molecular assays. Experience with fluorescence-based assay development. Experience with biochemical reconstitution of multi-component protein systems or signaling pathways. Experience with
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, dimension reduction, pathway analysis, survival analysis, and multivariable modeling. Strong analytical, organizational, and problem-solving skills. Ability to work independently while contributing
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August 1, 2028, with possibility of renewal based on continued availability of funding and performance. Minimum Required Qualifications Ph.D. or other terminal degree in relevant field Preferred
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computing, cloud-based computing environments, workflow-management systems, containers, and/or software development practices. Experience with machine learning, predictive modeling, or artificial intelligence
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theory, analysis of Roman commissioning and early GBTDS data, support for event-analysis and planet occurrence-rate pipelines, and the publication of scientific results based on Roman exoplanet data