Postdoc: ML-Driven Materials Modeling & DEM for Pharma

New Jersey Institute of Technology; Newark (NJ); On-site; USD 57,000 - 70,000; Full time

Job summary

New Jersey Institute of Technology in Newark invites applications for a Post Doctoral Research Associate in Chemical and Materials Engineering. The ideal candidate has a strong mathematical, physics and engineering background, excellent computational skills, and the ability to integrate experimental work into modeling.

The role emphasizes ML-accelerated characterization, DEM-based modeling, and ML surrogates to speed up pharmaceutical unit operations, with collaboration across CIMSEPP and

Qualifications

• Ph.D. in Engineering with substantial mathematical modeling experience.
• Experience with modeling granular materials transport and DEM is a plus.
• Strong programming skills and ability to implement data analysis workflows in Python.

Responsibilities

• Develop ML-accelerated workflow for characterization of microscopic surface roughness and shape morphology.
• Integrate experimental data into a coarse-grained DEM/modeling framework.
• Design ML surrogates and coarse-graining strategies to accelerate DEM for pharmaceutical unit operations.
• Supervise undergraduate and Master's students on related projects.
• Be the main contact for mathematical modeling and computational methods.
• Disseminate results through publications and conferences.

Skills

Machine learning

Python programming

Mathematical modeling

Computational modeling

Education

Ph.D. in Engineering

Tools

DEM software

Python programming

Job description

New Jersey Institute of Technology in Newark invites applications for a Post Doctoral Research Associate in Chemical and Materials Engineering. The ideal candidate has a strong mathematical, physics and engineering background, excellent computational skills, and the ability to integrate experimental work into modeling.

The role emphasizes ML-accelerated characterization, DEM-based modeling, and ML surrogates to speed up pharmaceutical unit operations, with collaboration across CIMSEPP and