USDA-ARS SCINet Postdoctoral Fellowship in Protein Folding and Structure: California

U.S. Department of Agriculture (USDA)
Albany, California
Job Category
Post Doctoral Appointments
Competitive Monthly Stipend
Last Date to Apply
*Applications will be reviewed on a rolling-basis and this posting could close before the deadline. ARS Office/Lab and Location: A postdoctoral research opportunity is available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), Produce Safety & Microbiology Research Unit located in Albany, California. Research Project: The U.S. Department of Agriculture - Agricultural Research Service (USDA ARS) mission involves problem-solving research in the widely diverse food and agricultural areas encompassing plant production and protection; animal production and protection; natural resources and sustainable agricultural systems; and nutrition; food safety; and quality. The programs are conducted in 46 of the 50 States, Puerto Rico, and the U.S. Virgin Islands. For ARS to maintain its standing as a premier scientific organization, major investments in computing, networking, and storage infrastructure are required. Training in data and information management are integral to the integrity, security, and accessibility of research findings, results, and outcomes within the ARS research enterprise. Nearly 2000 scientists and support staff conduct research within the ARS research enterprise. The SCINet/Big Data Research Participation Program of the USDA ARS offers research opportunities to motivated postdoctoral fellows interested in collaborating on agricultural-related problems at a range of spatial and temporal scales, from the genome to the continent, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning, to help solve complex agricultural problems that also depend on collaboration across scientific disciplines and geographic locations. In addition, many of these technologies rely on the synthesis, integration, and analysis of large, diverse datasets that benefit from high performance computing clusters (HPC). The objective of this fellowship is to facilitate cross-disciplinary, cross-location research through collaborative research on problems of interest to each applicant and amenable to or required by the HPC environment. Training will be provided in specific AI, machine learning, deep learning, and statistical software needed for a fellow to use the HPC to analyze large datasets. Under the guidance of a mentor, the participant will have the opportunity to gain experiences performing computational simulations on the folding and predicted 3D structures of proteins of microorganisms (bacteria, viruses, fungi, etc.) using Alphafold2 (and other software tools, e.g. RoseTTAFold) to better understand their structures and functions. Results of computational structural analysis will be compared with experimental data collected by mass spectrometry-based proteomic analyses. No prior experience in mass spectrometry or proteomics is required for this position (although such experience is a plus). Learning Objectives: The participant will learn HPC computing technologies and will help develop and co-lead ARS-wide workshops, resulting in a community of scientific practice on computational prediction of protein folding and 3D protein structures. The participant will have the opportunity to collaborate with multiple USDA ARS scientists on utilizing computational protein structure predictions to shed light on protein function as well as the impact of post-translational modifications on protein structures/functions and to write collaborative scientific papers on the results of such investigations. USDA-ARS Contact: If you have questions about the nature of the research, please contact Clifton Fagerquist ( Anticipated Appointment Start Date: As soon as a qualified candidate is identified. Start date is flexible and will depend on a variety of factors. Appointment Length: The appointment will initially be for one year, but may be renewed upon recommendation of the mentor and ARS, and is contingent on the availability of funds. Level of Participation: The appointment is full-time. Participant Stipend: The participant(s) will receive a monthly stipend commensurate with educational level and experience. Citizenship Requirements: This opportunity is available to U.S. citizens only. ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and ARS. Participants do not become employees of USDA, ARS, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE. Questions: Please visit our Program Website. If you have additional questions about the application process please email and include the reference code for this opportunity.
The qualified candidate should have received a doctoral degree in one of the relevant fields listed below. Preferred skills: Experience in protein bioinformatics and/or computational protein structure analysis Experience in 3D structural modeling of synthetic and/or natural biomolecules Prior computational modeling of protein structures a plus Proficiency in Linux and/or other state-of-the-art computational programming languages Strong oral and written communication skills
Contact Person
Bookmark the permalink.

Comments are closed.