Post Doctoral Associate-Radiology AI

University of Pittsburgh; Pittsburgh (Allegheny County); On-site; USD 60,000 - 85,000; Full time

Job summary

The University of Pittsburgh's Department of Radiology is seeking a Postdoctoral Research Associate to join an interdisciplinary team focused on artificial intelligence and computational methods for medical data analysis, including medical image analysis and multimodal data integration.

The position provides mentorship, opportunities to develop an independent academic research program, and collaboration with clinicians and other researchers.

Qualifications

• PhD or equivalent degree in computer science, AI, biomedical engineering, electrical engineering, applied mathematics, statistics, or a closely related field.
• Strong foundation in machine learning, deep learning, computational image analysis, statistical modeling, or medical data analysis.
• Demonstrated independent research ability and scholarly productivity, including peer-reviewed publications or comparable research output.
• Experience with scientific programming and computational research tools; proficiency in Python or similar languages is preferred.
• Strong motivation to develop reliable and clinically relevant AI methods and pursue an independent research career.
• Excellent written and oral communication skills in English, with the ability to work effectively in multidisciplinary teams.

Responsibilities

• Conduct original research under the guidance of the principal investigator while progressively developing research independence.
• Develop, implement, and evaluate machine learning and computational methods for the analysis of medical data.
• Prepare, preprocess, organize, and integrate medical datasets; maintain reliable and reproducible analysis workflows.
• Design and conduct experiments, evaluate model performance, perform statistical analyses, and interpret research findings.
• Collaborate with faculty, clinicians, and other researchers to define research questions and align computational methods with biomedical needs.
• Prepare and submit scientific manuscripts and conference abstracts; communicate results through presentations and research meetings.
• Participate in laboratory discussions, scientific seminars, and collaborations with other research groups.
• Contribute to grant proposals, research protocols, technical reports, and the development of new research directions.
• Maintain research code and documentation and follow applicable standards for research integrity, privacy, and data security.
• Provide guidance to students and junior researchers and assist with collaborative projects when appropriate.

Skills

Machine learning

Deep learning

Statistical modeling

Medical data analysis

Python programming

Education

PhD or equivalent degree in computer science, AI, biomedical engineering, EE, applied mathematics or statistics

Tools

Python

Job description

Post Doctoral Associate-Radiology AI

Med-Radiology - Pennsylvania-Pittsburgh (26006620)

Postdoctoral Associate Position in Medical AI and Data Analysis

The Department of Radiology at the University of Pittsburgh is seeking a highly motivated Postdoctoral Research Associate to join an interdisciplinary research team focused on artificial intelligence and computational methods for medical data analysis. The research aims to develop and evaluate data-driven approaches that extract meaningful information from diverse medical datasets and support biomedical discovery.

This position is designed for researchers with doctoral training in computer science, biomedical engineering, applied mathematics, statistics, or related quantitative fields who seek advanced research experience, close mentorship, and opportunities to develop an independent academic research career.

The postdoctoral researcher will work with faculty investigators, clinicians, and other research collaborators at the University of Pittsburgh. Research activities may include medical image analysis, multimodal medical data integration, predictive modeling, and the development of reliable and generalizable machine learning methods.

The fellow will participate in the design and execution of research projects, including data preparation, computational model development, experimental evaluation, statistical analysis, and interpretation of results. Responsibilities will include preparation of abstracts and manuscripts, presentation of research findings, and contributions to research proposals and study protocols. The fellow will attend regular research meetings and seminars and collaborate with investigators within and outside the university.

The appointment provides mentorship in study design, scientific writing, research methodology, interdisciplinary collaboration, and academic career development. The fellow is expected to take increasing ownership of research projects, produce peer-reviewed publications, and contribute new ideas to the research team. Opportunities to mentor students and develop independent proposals may be available.

Applicants must hold a PhD or equivalent degree before the appointment begins. Candidates should demonstrate strong computational and analytical skills, a clear interest in medical AI research, excellent English communication skills, and the ability to work independently while contributing effectively to multidisciplinary teams.

The position offers access to collaborative research resources, computing infrastructure, and faculty mentorship. Compensation, benefits, and other appointment terms will be determined in accordance with university policies and confirmed in the formal offer.

Applicants should submit a curriculum vitae, a brief statement of research interests and career goals, and a representative writing sample such as a published paper or academic manuscript. Letters of recommendation may be requested after initial review.

Qualifications and Expectations:

• PhD or equivalent degree in computer science, artificial intelligence, biomedical engineering, electrical engineering, applied mathematics, statistics, or a closely related field.


• Strong foundation in machine learning, deep learning, computational image analysis, statistical modeling, or medical data analysis.


• Demonstrated independent research ability and scholarly productivity, including peer-reviewed publications or comparable research output.


• Experience with scientific programming and computational research tools; proficiency in Python or similar languages is preferred.


• Strong motivation to develop reliable and clinically relevant AI methods and pursue an independent research career.


• Excellent written and oral communication skills in English, with the ability to work effectively in multidisciplinary teams.

Primary Responsibilities:

• Conduct original research under the guidance of the principal investigator while progressively developing research independence.


• Develop, implement, and evaluate machine learning and computational methods for the analysis of medical data.


• Prepare, preprocess, organize, and integrate medical datasets; maintain reliable and reproducible analysis workflows.


• Design and conduct experiments, evaluate model performance, perform statistical analyses, and interpret research findings.


• Collaborate with faculty, clinicians, and other researchers to define research questions and align computational methods with biomedical needs.


• Prepare and submit scientific manuscripts and conference abstracts; communicate results through presentations and research meetings.


• Participate in laboratory discussions, scientific seminars, and collaborations with other research groups.


• Contribute to grant proposals, research protocols, technical reports, and the development of new research directions.


• Maintain research code and documentation and follow applicable standards for research integrity, privacy, and data security.


• Provide guidance to students and junior researchers and assist with collaborative projects when appropriate.

The University of Pittsburgh is an equal opportunity employer / disability / veteran.

Assignment Category: Full-time regular

Campus: Pittsburgh

Child Protection Clearances: Not Applicable

Required Attachments: Curriculum Vitae

Assignment Category: Full-time regular

Equal employment opportunity, including veterans and individuals with disabilities.