Postdoc: ML-Driven Materials & Pharma Modeling

New Jersey Institute of Technology; York Township (IA); On-site; USD 57,000 - 70,000; Full time

Job summary

New Jersey Institute of Technology in Newark seeks a Post Doctoral Research Associate in Chemical and Materials Engineering. The candidate will develop ML-accelerated workflows to characterize microscopic surface roughness and integrate this with DEM-based particle flow models for pharmaceutical materials.

The position involves independent work, supervision of students, collaboration with CIMSEPP, and publication of results.

Qualifications

• A Ph.D. in Engineering with significant mathematical modeling experience
• Strong experience in modeling granular materials transport processes. Experience in discrete element model (DEM). Experience and interest in related experiments is a plus.
• Excellent skills in programming and implementation of data analysis workflows in Python.

Responsibilities

• Develop a workflow for machine learning-accelerated characterization of microscopic surface roughness and shape morphology of crystalline, spray dried and/or amorphous solid dispersions.
• Integrate this information with property prediction tools coupled with experimentally measurable quantity into a coarse-grained mathematical model of adhesion for particle-scale discrete element simulation of particle flow in the testing and manufacturing equipment used in pharmaceutical research and industry. Example systems of interest include: (1) categorization of spray-dried dispersions (SDDs) to be able to add a ML layer for a hybrid particle property prediction system; (2) DEM simulations of simple geometries to study mixing and segregation of particle systems.
• Leading the development, calibration, and validation of computational workflows to quantify microscopic surface roughness from stereomicroscopic data
• Integrating experimental data, knowledge, and material parameters into the discrete element modeling (DEM) framework.
• Design and implement machine learning surrogates and coarse-graining strategies to accelerate DEM for industrially relevant pharmaceutical unit operations
• Supervision of undergraduate and Master’s degree students on their related projects.
• Be the main point of contact (POC) for all mathematical modeling and computational methods.
• Disseminate results through peer-reviewed publications, conference presentations, and reports to the CIMSEPP Industrial Advisory Board (IAB).

Skills

Machine Learning

Python programming

Mathematical modeling

Computational workflows

DEM modeling

Education

Ph.D. in Engineering

Tools

DEM framework

Job description

New Jersey Institute of Technology in Newark seeks a Post Doctoral Research Associate in Chemical and Materials Engineering. The candidate will develop ML-accelerated workflows to characterize microscopic surface roughness and integrate this with DEM-based particle flow models for pharmaceutical materials.

The position involves independent work, supervision of students, collaboration with CIMSEPP, and publication of results.