Postdoctoral Researcher Position: Computational Modeling and Machine Learning of PFAS Surfactants
Position Overview:
We are seeking a highly motivated and skilled Postdoctoral Researcher to join our research group at the University of Puerto Rico – Mayagüez in an exciting project focusing on the development of computational and machine learning models to predict the self-assembly of PFAS surfactants. This position offers an excellent opportunity to work at the intersection of molecular simulations and machine learning in collaboration with Purdue University. The research aims to enhance our understanding of PFAS behavior in various environments, contributing to potential risk mitigation strategies.
The project is sponsored by the Strategic Environmental Research and Development Program (SERDP), a collaborative initiative involving the U.S. Department of Defense (DoD), the Department of Energy (DOE), and the Environmental Protection Agency (EPA). SERDP focuses on addressing environmental challenges related to the defense mission through innovative research and technology development.
Project Description:
The postdoctoral researcher will primarily focus on the following objectives:
Molecular Dynamics (MD) Simulations: Employ MD simulations to study the self-assembly of PFAS surfactants with various chemical structures in aqueous solutions.
Brownian Dynamics (BD) Simulations: Conduct BD simulations to model the diffusion dynamics of PFAS surfactants, focusing on larger systems over longer timescales.
Machine Learning (ML) Integration: Develop and implement ML algorithms to predict PFAS behavior based on experimental and simulation data.
Platform Development: Contribute to the creation of an open and accessible platform for storing, sharing, and processing data related to PFAS surfactants.
Qualifications:
Ph.D. in Computational Chemistry, Chemical Engineering, Materials Science, Physics, or a related field.
Strong background in Molecular Dynamics (MD) and/or Brownian Dynamics (BD) simulations.
Experience with machine learning algorithms and data analysis.
Proficiency in using molecular simulation software (e.g., GROMACS) and programming languages (e.g., Python).
Excellent communication skills and ability to work collaboratively in a multidisciplinary environment.
Compensation:
Annual salary of $50,000 plus fringe benefits.
The position is expected to start in early 2025. The appointment is for one year, with the possibility of extension based on progress and satisfactory performance.
Application Process:
Interested candidates should submit the following documents:
A cover letter detailing research experience and interests.
A current CV.
Evidence of having obtained a PhD, such as a diploma or certification.
Three letters of recommendation from former advisors or collaborators.
Contact Information:
For inquiries and to submit your application, please contact Dr. Ubaldo M. Córdova-Figueroa at ubaldom.cordova@upr.edu. Applications will be reviewed on a rolling basis until the position is filled.
