Postdoc / Data Manager

University of Kansas

Kansas (Remote work possible), USA 🇺🇸


The Aquatic Intermittency effects on Microbiomes in Streams (AIMS) project seeks applications for a 50% Postdoctoral Associate / 50% Data Coordinator position. We are looking for motivated, energetic, and creative recent Ph.D. biologists, biogeochemists, data analysists or hydrologists to join our team of 50 collaborators. This multi-institutional interdisciplinary research program spans four states (KS, ID, AL, MS) and eight institutions (University of Kansas, Haskell Indian Nations University, Kansas State Univ., Idaho State, Univ of Alabama, Alabama A&M, Southern Mississippi Univ, Univ of Mississippi). Additional information about the AIMS Project can be found on our Open Science Framework site. Data manager duties include collating and managing data collected by the project, working with the project’s investigators to design and deliver data products to long-term open access repositories, training graduate and undergraduate students to track and QA/QC the various types of project data. In addition to the duties of data coordination, we are looking for an interested postdoctoral candidate with compelling research ideas that can leverage existing data generated by the project. This position will be expected to conduct research in collaboration with AIMS member(s) and disseminate research results to the scientific community including leading collaborative manuscripts and presenting project data at state, national, and international conferences. Expertise in environmental sensor, sequencing data and/or geospatial data is required. This position will be based at the University of Kansas in Lawrence, KS, but exceptional candidates with remote-work only requirements will be considered. The position is available immediately and will be hired on a one-year contract, with the expectation of renewal for a second year pending satisfactory performance.

Job Description
Post-Doctoral Research (50%)
The postdoctoral researcher will conduct research at the intersection of hydrology, biogeochemistry, and microbial ecology in intermittent stream ecosystems, and will develop a specific research program in at least one of these areas in collaboration with relevant project investigators. Specific job duties under the postdoctoral researcher category include:
1. Conduct analyses using AIMS’ core datasets with preference given to analyses that can combine two or more types of data generated on the project.

2. Prepare and present updates on on-going research and analyses for various sub-groups of the larger AIMS project.

3. Participate in group meetings, seminars, workshops, and conferences.

4. Assist with the mentoring and training of graduate students across the AIMS project.

5. Maintaining a current understanding of the literature and how AIMS’ contributions fit in.

Data Management (50%)
The AIMS Data Manager will maintain a data management system to collate and organize data (biogeochemical, environmental sequencing, and geospatial data) and metadata (field and laboratory). This may include but is not limited to:
1. Implement the data management plan outlined in the project proposal

2. Work with and refine the current AIMS data management system

3. Communicate with project members about expectations of data management plan, including answering questions and clarifying policies
a. Meeting regularly with AIMS’ regional and disciplinary groups to ensure data QA/QC, migration and storage follow protocols already in place

b. Training students and faculty in how to organize and access data

4. Facilitate, with others in the project, the (1) tracking of samples and data streams from the multiple sites across the project; (2) collation of data from field sites and laboratory experiments and implementing QA/QC procedures; (3) security and back ups of data; (4) accessibility of fully QA/QC’d data across the project in a timely manner.

5. Participate in organizing and teaching Carpentries workshops across the project.

6. Create or enhance an existing Carpentries teaching module as an AIMS product.

7. Facilitate the finalization of data products to be deposited in public repositories.






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