The postdoctoral researcher will apply computational methods to investigate relationships between mineral element electronegativity associations and protein cofactor chemistry. The researcher will focus on the chemical environment of protein folds (i.e., metal cofactor binding sites), by investigating the hydrophobicity/hydrophilicity of protein folds that occur in electron transfer proteins. Proteins that drive biological metabolism are constructed out of the same building block elements as many minerals. The researcher will work towards building a new understanding of how chemical elements associate with each other in minerals on the basis of their physical properties (ex: electronegativity), and how element associations in proteins drive their function. The postdoctoral researcher will use open source software/programming languages, such as R and/or Python, and other computational methods (e.g. protein structural modeling software) to characterize protein fold element associations with metal cofactors. Following protein fold characterization, the researcher will assemble mineral element electronegativity data for relevant metals that are incorporated as cofactors in protein folds and compare protein fold environment with mineral lattice environment for a particular element (primarily transition metals).

This position requires publication of research results, presentation at conferences, and participation in group meetings, in addition to research. 

The successful candidate will mentor student research in collaboration with the PIs of the grant and assist students in presentation and publication of their results. 

The successful candidate must be self- motivated, work well in a collaborative environment, including online meetings, and committed to supporting and respecting a diverse community of student, faculty, and staff.  

Minimum qualifications:

The successful candidate must have a Ph.D in biology, environmental science, geology, or a related field. Applicants with interdisciplinary biogeochemical research experience are preferred. 

The successful candidate must have computational research experience using open source software. 

The successful candidate will have a demonstrated publication record.

Note: 

• Rowan University is an Equal Opportunity Employer and values diverse people and abilities. Reasonable accommodations will be made to enable individuals with disabilities to perform the essential functions of this position.
• Candidates must be legally authorized to work in the US, and the university will not sponsor an applicant for a work visa for this position.
• Only completed online applications submitted on or before the posted deadline will be considered.