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Medical Ai Postdoc Jobs (NOW HIRING)

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX

$46K - $63K/yr

... AI)/deep learning technologies, mathematical biomechanical modeling, inverse problems, and ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX

$46K - $63K/yr

... AI)/deep learning technologies, mathematical biomechanical modeling, inverse problems, and ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX · On-site

$46K - $63K/yr

... AI)/deep learning technologies, mathematical biomechanical modeling, inverse problems, and ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

Statistics Interest Group

... Medical School, the Michigan Institute for Data Science, and other research groups across the ... The position will focus on developing and applying novel statistical, machine-learning, and AI ...

Duke University

Postdoctoral Associate

Durham, NC · On-site

Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive ... This postdoctoral research position focuses on applying AI, agentic systems, and software ...

Duke University

Postdoctoral Associate

Durham, NC · On-site

Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive ... This postdoctoral research position focuses on applying AI, agentic systems, and software ...

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Medical Ai Postdoc information

What is a medical AI postdoc?

A Medical AI Postdoc is a postdoctoral researcher who specializes in applying artificial intelligence (AI) techniques to healthcare and medical research. Their work often involves developing machine learning models, analyzing medical data, and collaborating with clinicians to improve diagnostics, treatment planning, or patient outcomes. Medical AI Postdocs typically hold a PhD in computer science, biomedical engineering, data science, or a related field, and have expertise in both AI methodologies and medical applications. The position is usually a temporary academic or research role designed to further deepen expertise and contribute to scientific advancements in medical AI.

What are the typical collaborative opportunities for a medical AI postdoc within academic and clinical research settings?

Medical AI Postdocs often work in interdisciplinary teams, collaborating closely with clinicians, data scientists, and other researchers to develop and validate AI-driven healthcare solutions. This role typically involves attending regular lab meetings, participating in joint research projects, and contributing to multi-institutional studies. Effective communication and teamwork are essential, as you may be responsible for translating complex AI concepts to non-technical stakeholders and integrating clinical feedback into model development. These collaborations not only enhance research impact but also provide valuable networking and professional development opportunities.

What are the key skills and qualifications needed to thrive as a medical AI postdoc, and why are they important?

To thrive as a Medical AI Postdoc, you need a strong background in machine learning, biomedical data analysis, and programming, typically demonstrated by a PhD in a relevant field such as computer science, biomedical engineering, or computational biology. Familiarity with tools like Python, TensorFlow, PyTorch, and experience working with medical datasets or electronic health records is highly valuable. Exceptional problem-solving skills, scientific communication, and interdisciplinary collaboration set standout candidates apart. These competencies are crucial for advancing medical AI research, translating findings into clinical applications, and fostering innovation within a multidisciplinary environment.

What is the difference between Medical Ai Postdoc vs Medical Data Scientist?

AspectMedical Ai PostdocMedical Data Scientist
Required CredentialsPhD in AI, Machine Learning, or related field; research experienceMaster's or PhD in Data Science, Statistics, or related field; programming skills
Work EnvironmentAcademic or research institutions, labsHospitals, healthcare companies, biotech firms
Employer & Industry UsageResearch projects, academic grantsClinical data analysis, healthcare product development
Common Search & Comparison IntentResearch roles, academic positionsIndustry roles, applied data analysis

The Medical Ai Postdoc typically focuses on academic research, developing new AI methods for healthcare, often within universities or research labs. In contrast, a Medical Data Scientist applies data analysis techniques directly to clinical data in healthcare settings, focusing on practical applications and product development. Both roles require strong technical skills but differ mainly in their work environment and end goals.

What are popular job titles related to Medical Ai Postdoc jobs?

For Medical Ai Postdoc jobs, the most frequently searched job titles are:

Infographic showing various Medical Ai Postdoc job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 77% Full Time, 15% Part Time, and 7% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

POSTDOCTORAL RESEARCHER-HDSB-Xiao Lab-[Req#: 914775, Position#: 123269]

Dallas, TX • On-site

UT Southwestern Medical Center
Hospitals • 10K+ employees
Learn more about UT Southwestern Medical Centerexternal

Full-time

Re-posted 23 days ago

UT Southwestern rating

7.9

Company rating: 7.9 out of 10

Based on 152 frontline employees who took The Breakroom Quiz

Job description

Description
A postdoctoral fellow position in AI and Data Science is now available in the laboratories of Dr. Guanghua Xiao at the Quantitative Biomedical Research Center in the Peter O'Donnell School of Public Health at UT Southwestern Medical Center at UT Southwestern Medical Center at Dallas.
The Quantitative Biomedical Research Center (QBRC) is a well-established interdisciplinary research center at UT Southwestern that brings together experts in artificial intelligence, machine learning, predictive modeling, clinical informatics, digital pathology, and biomedical data science. Our goal is to develop cutting-edge computational methods and tools that enable novel discoveries and support data-driven decision-making in health care and public health.
We are seeking highly motivated, creative, and collaborative postdoctoral candidates to join our dynamic team and contribute to a portfolio of research projects applying AI and data science to real-world health care and public health data. The main research areas include:
• Electronic Health Records (EHR)
• Medical imaging (e.g., radiology and pathology)
• Real-time monitoring and wearable sensor data
The successful candidate will have the opportunity to lead and contribute to innovative projects in clinical prediction modeling, disease progression modeling, population health surveillance, and digital biomarker discovery. Our center also supports strong collaborations with clinicians, data scientists, and public health researchers.
Qualifications:
• Ph.D. in Computer Science, Statistics, Biomedical Informatics, Engineering, or a related field.
• Strong programming skills and experience with machine learning, deep learning, or AI applications.
• Interest or experience in working with large-scale health-related datasets.
Qualifications
Qualifications:
• Ph.D. in Computer Science, Statistics, Biomedical Informatics, Engineering, or a related field.
• Strong programming skills and experience with machine learning, deep learning, or AI applications.
• Interest or experience in working with large-scale health-related datasets.
Application Instructions
Application materials must be submitted through Interfolio.
Interested individuals must upload a CV, cover letter, and a list of three references.

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