Lab Data Coord : Seattle, WA, United States

Job ID: 574921
Job date: 2016-03-21
End Date:

Company : Fred Hutchinson Cancer Research Center 

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Role : Research Scientist 


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Job Description:
Fred Hutchinson Cancer Research Center, home of three Nobel laureates, is an independent, nonprofit research institution dedicated to the development and advancement of biomedical research to eliminate cancer and other potentially fatal diseases. Recognized internationally for our pioneering work in bone-marrow transplantation, the five scientific divisions at Fred Hutch collaborate to form a unique environment for conducting basic and applied science. Fred Hutch, in collaboration with its clinical and research partners, the University of Washington and Seattle Children’s, is the only National Cancer Institute-designated comprehensive cancer center in the Pacific Northwest. Join us and make a difference! About the Division & Research Program: The Vaccine and Infectious Disease Division (VIDD) was established as an institute at Fred Hutch in 2007 to facilitate and enhance the Hutch’s efforts in infectious disease prevention and vaccine development. The institute achieved Division status in 2010 and now has more than 50 faculty members and houses the HIV Vaccine Trials Network (HVTN) - the world’s largest clinical trials network for the development and testing of an HIV vaccine. Biostatistics, Bioinformatics, & Epidemiology (BBE) is a research program within the Vaccine and Infectious Disease Division of the Fred Hutch. With the goal being to eliminate the mortality and morbidity of infectious diseases, members of the program conduct quantitative scientific research employing biostatistics, bioinformatics, computational biology, infectious disease epidemiology, and mathematical modeling. Members of the program collaborate extensively with laboratory and clinical science colleagues both within the Hutch and provide leadership for statistical data management centers and modeling consortia worldwide. About SCHARP: As part of the BBE program in VIDD, The Statistical Center for HIV/AIDS Research & Prevention (SCHARP) provides statistical collaboration to infectious disease researchers around the world and conducts a complementary program of statistical methodology, and mathematical modeling research. SCHARP also collects, manages, and analyzes data from clinical trials and epidemiological studies dedicated to the elimination of infectious disease as a threat to human health. Current projects include studies to evaluate and implement prevention strategies for HIV, tuberculosis, polio, malaria and other globally important pathogens. Job Summary: We are looking for a Data Coordinator to join the SCHARP Laboratory Data Operations (LDO) group. Part of the SCHARP Data Management Unit (DMU), the LDO team is responsible for developing and maintaining the laboratory assay and specimen data pipelines for multiple clinical trials, pre-clinical studies and research and development projects. Primary projects include managing lab data from studies implemented by the HIV Vaccine Trials Network (HVTN), HIV Prevention Trials Network (HPTN), Microbicides Trials Network (MTN) and the Collaboration for AIDS Vaccine Discovery (CAVD). LDO Data Coordinators perform project and data coordination tasks related to assay data pipelines, work both independently and as part of a team, and are expected to communicate effectively with colleagues and be responsive to the needs of SCHARP staff as well as external collaborators as required. The day to day work will involve exercising technical expertise in developing and implementing data management practices and procedures essential to the validity of assay results from pre-clinical research studies and clinical trials. Responsibilities In support of research network operations, funding agency requirements, and organizational needs, the Lab Data Coordinator may perform some or all of the following tasks:

  1. Act as a liaison between SCHARP study teams and external collaborators to develop an understanding of laboratory procedures required in support of study objectives
  2. Coordinate laboratory data management procedures including data collection, transfer, processing, storage, and quality control practices
  3. Manage clinical and pre-clinical study-specific data pipelines including setting up and monitoring data transfers and coordinating with project managers, programmers, analysts and other stakeholders regarding timelines and deliverables.
  4. Review, design, produce and/or standardize laboratory data reports
  5. Investigate and resolve data discrepancies; work with external labs and other SCHARP staff to troubleshoot issues and develop necessary process improvements
  6. Assist in the development of tools and processes for use by external labs submitting data to SCHARP; may include development of templates, forms, macros and/or management of existing web-based data upload platforms
  7. Work with SCHARP section representatives and external collaborators to develop and implement training, policies, standard operating procedures, work practices, quality control methods and associated documentation
  8. Support Lab Data Operations programmers by assisting with the development of requirements and performing routine testing of applications used to manage lab data
  9. Serve as project coordinator for assay data management initiatives
  10. Perform other responsibilities as required
Qualifications Minimum qualifications:
  • Bachelor’s degree in Biological Sciences, Computer Science or similar degree in a scientific, technical or health-related field
  • Previous data management experience in a laboratory setting
  • Excellent written/verbal communication skills
  • Demonstrated ability to work independently and as part of a team and manage competing priorities in a fast-paced environment
Preferred qualifications:
  • Working knowledge of HIV biology and/or cellular/humoral immunology assays such as flow cytometry, multiplex bead array, ELISA, etc.
  • Experience with infectious disease prevention clinical trials or NHP pre-clinical studies
  • Understanding of current/standard approaches to data collection, processing of raw data into analysis datasets, and other downstream research activities is highly desirable
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