Postdoctoral Fellow (PREP0004499)

Johns Hopkins University; Baltimore (MD); On-site; USD 70,000 - 95,000; Full time

Job summary

Johns Hopkins University is seeking a PREP Research Associate to lead research on Artificial Intelligence for Forensic Firearm and Toolmark Analysis. The role involves developing AI methods to enhance accuracy and reproducibility in forensic science and translating findings into actionable standards.

Ideal candidates hold a Ph.D. or master’s degree in a relevant field, have research experience in AI/ML, and possess strong communication skills. This position offers the opportunity to collaborate with the forensic community and contribute to scientific publications.

Qualifications

• Ph.D. or master’s degree in a relevant field.
• Research experience in AI/ML for image analysis.
• Proficiency with Python or MATLAB.
• Strong oral and written communication skills.

Responsibilities

• Develop a research program on AI/ML in forensic analysis.
• Lead the development of a computational pipeline for toolmark images.
• Investigate AI/ML for toolmark image comparisons.
• Benchmark AI/ML against traditional examination methods.
• Quantify uncertainty of AI/ML outputs for courtroom testimony.
• Collaborate with the forensic community to translate findings.
• Publish findings and present at conferences.

Skills

Research experience in AI/ML for image analysis

Proficiency with Python

Proficiency with MATLAB

Strong oral communication skills

Strong written communication skills

Education

Ph.D. or master’s degree in computer science, physics, engineering, statistics, forensic science, or a closely related field

Job description

PREP Research Associate

PREP Research Associate

Research Title: Artificial Intelligence for Forensic Firearm and Toolmark Analysis

A researcher will lead the development, evaluation, and characterization of AI/ML methods to improve the objectivity, reproducibility, and accuracy of toolmark pattern evidence analysis. The work will address critical challenges in the application of AI/ML to forensic science, including transparency, robustness, bias, and uncertainty, and translate findings into standards‑based approaches.

Responsibilities

• Develop a forward‑looking research program on AI/ML in forensic firearm and toolmark analysis and collaborate on cross‑cutting techniques for other types of pattern evidence.
• Lead the development of a computational pipeline for the consistent segmentation of toolmark images using AI/ML methods.
• Investigate AI/ML to address major challenges in forensic toolmark analysis, such as characterizing toolmark quality and the direct comparison of toolmark images.
• Benchmark AI/ML‑assisted results against procedural algorithms and traditional examinations to identify where AI/ML can provide significant improvements in objectivity and efficiency.
• Quantify the uncertainty of AI/ML outputs to ensure objective communication of evidence strength in courtroom testimony and explore explainable AI frameworks that inform examiners on relevant features.
• Collaborate with the forensic community to translate research findings into actionable standards and best‑practice guides.
• Publish findings in peer‑reviewed journals and present results at scientific conferences.

Qualifications

• Ph.D. or master’s degree in computer science, physics, engineering, statistics, forensic science, or a closely related field.
• Research experience in the development and application of AI/ML for image analysis.
• Proficiency with Python or MATLAB.
• Evidence of independent research experience and a strong enthusiasm for learning new theoretical, computational, and experimental techniques.
• Strong oral and written communication skills.
• U.S. citizenship preferred.

Equal Opportunity Employer

The Institute is an equal opportunity employer and does not discriminate on the basis of protected characteristics.