Dramatic increases in the scale and availability of data are profoundly reshaping all domains in the life sciences. Data acquisition and availability from DNA sequencers, environmental sensors, parallel global studies, and imagery are outpacing our capacity for analysis, including the development of models that represent our knowledge of biological processes. Research in our consortium will develop and compete computational, statistical, and machine learning methods for multi-dimensional data to create predictive and explanatory models for the life sciences. The project focuses on three research areas: (1) connecting genome to phenome (particularly in the context of evolutionary biology), (2) mechanistic modeling of species interactions and community diversity, and (3) time series of material and energy flux in aquatic ecosystems.
The positions are 100% research with flexible start dates; however, preference will be given to candidates who will be able to join the consortium immediately. The positions are for two years, with the possibility for extending the appointment, contingent upon performance.
The postdoctoral researchers will be primarily based in one or a few labs but will benefit from the opportunities to collaborate broadly. The positions allow for multiple professional development opportunities, including training in highly interdisciplinary science, collaborations across institutions, regular meetings with the entire consortium, mentorship toward academic and non-academic career development, and interactions with graduate and undergraduate students.
Successful applicants are not expected to have expertise in all facets of the project, but rather may be experts in a given area of modeling or domain of the life sciences. The postdoctoral researchers will primarily analyze existing and simulated data, and will have additional, complementary opportunities for laboratory or field research. We recognize that the best science can originate from diverse collaborations with people from varied backgrounds, and we especially encourage applicants from underrepresented groups to apply. The positions are supported by a 4-year, $6 million NSF EPSCoR RII Track-2 grant in response to our proposal entitled Creating Explanatory, Process-Based Models to Harness the Data Revolution in the Life Sciences.
To apply, submit a cover letter stating your interest in the position and previous experience as it relates to the position, including each of the preferred qualifications. Also, provide a CV, links to 1–2 recent first-authored publications, and names and contact information for three professional references. Review of applications will begin at slightly different times for the different institutions (as early as late October) and will continue until the positions are filled.