Postdoctoral Fellow, Accelerated Material Development for 3D Printing

St. Francis Xavier University; Ottawa; On-site; CAD 60,000 - 80,000; Full time

Job summary

A leading research institution in Canada is offering a Postdoctoral Fellowship focused on integrating artificial intelligence with materials development for advanced 3D printing technologies. The successful candidate will leverage machine learning methods and extensive datasets to aid in creating new photoresins for various applications. Candidates must hold a PhD in a relevant field and have significant experience in polymerization processes and additives. This position offers a competitive salary and benefits, as well as a supportive travel fund.

Benefits

Travel fund to support research

Opportunity for career development through publications

Qualifications

• Significant experience in polymerization reactions and 3D printing/additive manufacturing techniques.
• Experience with materials characterization methods such as MicroCT and FTIR spectroscopy.
• Familiarity with machine learning or AI approaches for materials development.

Responsibilities

• Integrate AI with materials development for tomographic volumetric additive manufacturing.
• Use predictive AI models linking photoresin formulation and printing conditions.
• Guide the design of new photoresins for precision and scalability.

Skills

Polymerization reactions

3D printing/additive manufacturing

Machine learning / AI

Data collection and analysis

Education

PhD in polymer, chemistry, materials science and engineering, chemical engineering

Tools

Python

MATLAB

R

Julia

SolidWorks

Job 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.

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