Location: Pittsburgh, Pennsylvania
The Brain Image Library (BIL), is the NIH-designated microscopy archive for the BRAIN Initiative. The data scope of the BIL includes whole-brain microscopy image datasets and their accompanying secondary data such as neuron morphologies, targeted microscope-enabled experiments including connectivity between cells, spatial transcriptomics, and historical collections of value to the community. The collection currently contains thousands of mouse brain datasets, and to a lesser extent, datasets from primates. The technologies most frequently used to generate the data currently deposited in the library include serial two-photon tomography (STPT), fluorescence micro-optical sectioning tomography (fMOST), oblique light-sheet tomography (OLST) and others.
Carnegie Mellon University's Pittsburgh Supercomputing Center is searching for a Data Curator and Metadata Librarian. This is an excellent opportunity for someone who thrives in an interesting and challenging work environment. You will contribute to the department by providing critical support by curating the data deposited in BIL. The DCML will interact with data depositors and users on a frequent basis and participate in efforts to develop community data and metadata standards. The DCML will lead continuous improvement efforts to ensure that the data deposited in the BIL is increasingly FAIR. The DCML will also establish interconnecting metadata linkages from BIL to other data repositories.
Core responsibilities will include:
Understand FAIR principles and their application to digital data.
Possess familiarity with commonly used ontologies within the research community
Conduct quality assurance tests on repository metadata and resolve errors with data contributors
Represent and advocate for repository interests in relevant working groups and standardization efforts.
Communicate effectively with the research community
Conduct periodic quality assurance tests of the BIL and resolve errors discovered with data contributors.
Curate BIL metadata to resolve errors, reflect new standards, and to ensure FAIR compliance.
Participate, represent, and advocate for BIL interests in relevant community working groups and standardization efforts.
Integrate and add annotation data to existing data in the data repository.
Link data in BIL to relevant external data repositories, resources, and related datasets.
Work with relevant repositories to harmonize metadata to facilitate exchange and reuse of data.
Provide BIL help-desk support and documentation concerning metadata.
Other duties as assigned
You must demonstrate:
Knowledge of biological image data, commonly used ontologies and standards, and excellent interpersonal skills. Knowledge of scripting and/or SQL would be helpful, but not required.
Flexibility, excellence, and passion are vital qualities within the Mellon College of Science. Inclusion, collaboration and cultural sensitivity are valued competencies at CMU. Therefore, we are in search of a team member who is able to effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.
Bachelor's degree in Biology, Medicine, Information/Library science, Data Science, Computer Science or related field required; Masters Degree or advanced degree preferred
3-5 years of experience in information technology, healthcare, business, or research field is required. Experience with genomics or bioinformatics is preferred.
Experience with other programming languages used in data science (such as Python or R) is valuable.
Extensive experience managing/preparing data sets for use in analysis, modeling, or business operations is required.
Experience and technical proficiency in SQL is preferred.
Experience with biological data management is preferred.
Experience organizing public events and conducting training sessions and workshops.
Are you interested in this exciting opportunity? Please apply!
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Staff - Regular
Full Time/Part time
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