Description

The program
The NRC’s Postdoctoral Fellowship program offers PDFs access to unique world-class facilities and the opportunity to work alongside multi-disciplinary teams of expert researchers and technicians on projects of critical importance to Canada. PDFs will carry out research on innovative research projects, with opportunities for career development (publications and/or industry interaction).

PDFs will be offered appointments to the staff of the National Research Council on a term basis and will be offered salaries and benefits currently available to Research Officers. Salaries commensurate with experience are taxable and subject to other deductions. As a guide, the current annual PhD recruiting rate is $83,985. In addition PDFs will be allocated a travel fund to support their work.

Project title
An AI-Driven Framework to Screening for High Performance Photoresins used with Volumetric 3D Printing

The role
Tomographic volumetric additive manufacturing (TVAM) is an emerging 3D printing technology that creates entire objects in a single step by projecting light patterns into a volume of photoresin. This approach enables fast, high-resolution, support-free fabrication of complex geometries, well beyond the capabilities of conventional additive manufacturing. To fully realize TVAM’s potential across advanced manufacturing sectors, advances in both photoresin formulation and automated process control are essential. This postdoctoral project will integrate artificial intelligence (AI) with materials development to address these challenges. The Fellow will use predictive AI models that link photoresin formulation, printing conditions, and print fidelity, leveraging NRC’s extensive TVAM dataset. These insights will guide the design of new photoresins targeted for diverse applications with precision, reproducibility, and scalability. The outcome is an AI-enabled framework for accelerating materials discovery and automated, high-quality TVAM printing.

Requirements

Education
PhD in polymer, chemistry, materials science and engineering, chemical engineering, or a closely related field (e.g., nanotechnology, biomedical engineering, computational materials science with materials background).

Experience

• Significant experience in polymerization reactions and 3D printing/additive manufacturing techniques;
• Significant experience using any of the following (the more the better) materials characterization methods:
  • MicroCT
  • FTIR spectroscopy
  • Photo-rheometry
  • Tensile and compression testing
  • UV–Vis spectroscopy
  • Surface profilometry
  • Optical microscopy
  • Scanning electron microscopy (SEM)
• Experience using or working with machine learning / AI approaches for materials development or process optimization; and
• Experience in data collection, analysis, and processing.

Assets:

• Experience using Python or another scientific programming language (e.g., MATLAB, R, Julia);
• Experience with relevant software tools for modeling, visualization, and analysis (e.g., MeshLab, SolidWorks, ImageJ).

Language requirements
English