The Cremins lab works at the spatial biology-technology interface to understand chromatin-to-synapse communication during neural circuit activation in the mammalian brain. We aim to understand how chromatin works through long-range physical folding mechanisms to encode neuronal specification and long-term synaptic plasticity in healthy and diseased neural circuits. We pursue a multi-disciplinary approach integrating data across biological scales in the brain, including molecular Chromosome-Conformation-Capture sequencing technologies, single-cell imaging, optogenetics, genome engineering, induced pluripotent stem cell differentiation to neurons/organoids, and in vitro and in vivo electrophysiological measurements. Our long-term scientific goal is to dissect the fundamental mechanisms by which chromatin architecture causally governs genome function and, ultimately, long-term synaptic plasticity and neural circuit features in healthy mammalian brains as well as during the onset and progression of neurodegenerative and neurodevelopmental disease states. Our long-term mentorship goal is to develop a diverse cohort of next-generation scientists cross-trained in molecular and computational approaches. We seek to create a positive, high-energy environment with open and honest communication to empower individuals to discover and refine their purpose and grow into the best versions of themselves. The candidate will work with a dynamic team of graduate students to develop new code and statistical methods to analyze newly created data in the Cremins lab to map the neural connectome at synapse resolution. Imaging data includes in situ sequencing signals procured across hundreds of fields of view. Pipelines to be developed will focus on base calling of nucleotides, cell segmentation, registration of spots across cycles, drift correction, and assembly of barcode counts files, and the interpretation of barcodes as a given neuron in specific x, y, z coordinates. Candidates will be expected to organize, manage, and curate the imaging data to make it available to the scientific community on public portals. All code should be written by PEP8 standards and of quality to provide it freely available to the community via bitbucket. This role is ideal for you if you have a strong interest and motivation toward working with new data never produced or analyzed before, and thrive in a fast paced environment discovering new answers. Candidates will independently search the published literature and available code to develop a portfolio of novel computational tools for processing multi-modal imaging data. The candidate will contribute to the preparation of multiple manuscripts, including making figures and writing methods and results. This role is ideal for you if you enjoy the excitement of a bleeding-edge scientific laboratory and welcome the challenge of a fast-paced environment and working collaboratively in a positive, warm, and community-focused scientific culture. Ideal for post-baccalaureate students eager to do PhD level research.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Master's degree