Postdoctoral: Computational Modeling: Exciting opportunity for a highly motivated and skilled Postdoctoral Researcher to join our research group at the University of Puerto Rico – Mayagüez. This position involves working on computational and machine learning models to predict the self-assembly of PFAS surfactants in collaboration with Purdue University.
Postdoctoral Researcher Position: Computational Modeling and Machine Learning of PFAS Surfactants
Designation: Postdoctoral Researcher
Research Area: Computational Modeling and Machine Learning of PFAS Surfactants
Location: University of Puerto Rico – Mayagüez
Eligibility/Qualification:
- 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.
Job Description:
- Utilize MD simulations to study the self-assembly of PFAS surfactants with various chemical structures in aqueous solutions.
- Conduct BD simulations to model the diffusion dynamics of PFAS surfactants, focusing on larger systems over longer timescales.
- Develop and implement ML algorithms to predict PFAS behavior based on experimental and simulation data.
- Contribute to the creation of an open and accessible platform for storing, sharing, and processing data related to PFAS surfactants.
How to Apply:
Interested candidates should submit the following documents to Dr. Ubaldo M. Córdova-Figueroa at ubaldom.cordova@upr.edu:
- 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.
Last Date for Apply: Applications will be reviewed on a rolling basis until the position is filled.
