Posted to IASSIST on: 2023-04-25
Employer: University of Rhode Island
Employer URL: https://uri.edu/
Description
STEEP (Sources, Transport, Exposure & Effects of PFAS), established in 2017, a Multiproject Center Grant awarded by the National Institute of Environmental Health Sciences Superfund Research Program (NIEHS SRP), is a partnership of the University of Rhode Island, Harvard University, and Silent Spring Institute.
STEEP addresses the threat of poly- and perfluoroalkyl substances (PFAS) through rigorous interdisciplinary science exploring:
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transport and exposure pathways
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impacts on human health
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mechanisms for uptake, elimination, and screening
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novel environmental detection techniques
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engagement with communities at contaminated sites
We are seeking a highly motivated Post-Doctoral Research Fellow to join our interdisciplinary team. The primary responsibility of this position will be to develop and implement data management practices based on the FAIR (Findable, Accessible, Interoperable, and Reusable) principles for data collected from experiments, simulations, field research, and clinical studies. The successful candidate will work closely with project teams to ensure that data generated by the project are managed in a manner that promotes transparency, collaboration, and scientific rigor. Specifically, the Post-Doctoral Research Fellow will:
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Develop and implement data management plans and practices for the project in accordance with the FAIR principles.
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Work with the research team to ensure that data are properly documented, formatted, and curated to promote reusability and interoperability.
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Develop and maintain data sharing agreements and policies for the project.
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Ensure compliance with ethical and legal requirements related to data management and sharing.
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Participate in project meetings and collaborate with team members to advance the scientific goals of the project.
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Contribute to the preparation of scientific publications, reports, and presentations.
Qualifications:
REQUIRED
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PhD in a relevant field (e.g., environmental science, data science, public health, or related field)
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Strong background in data management and analysis
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Familiarity with the FAIR principles and best practices for data management and sharing
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Experience with Python or R for data analysis
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Excellent organizational and communication skills
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Ability to work independently and as part of a team
PREFERRED:
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Familiarity with LC-MS analysis
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Familiarity with proteomics and RNA sequencing data.
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Familiarity with XML or JSON
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Familiarity with the use of taxonomies, thesauri, and/or ontologies
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Experience working on interdisciplinary research projects is desirable
This is a full-time, 1-year position, with the possibility of extension based on funding and performance. The position offers a competitive salary and benefits package, and the opportunity to work on a high-impact, interdisciplinary research project.
Location
Kingston, RI
Archived on: 2023-05-26