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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 ...

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Medical Ai Postdoc information

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 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.
Infographic showing various Medical Ai Postdoc job openings in the United States as of June 2026, with employment types broken down into 100% Part Time. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.
Research Associate - FELIX Lab 2.0

Research Associate - FELIX Lab 2.0

Johns Hopkins University

Baltimore, MD • On-site

Full-time

Posted 27 days ago

Johns Hopkins Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 200 frontline employees who took The Breakroom Quiz

225th of 872 rated healthcare providers

Job description

Description
Position Summary:
The Felix Lab is seeking a highly motivated and detail-oriented Research Associate to join our team focused on the early detection of pancreatic neoplasms using artificial intelligence and advanced imaging analysis. The candidate will lead data management, contribute to ongoing multi-institutional collaborations, and play a key role in the development of AI-driven diagnostic tools that improve early detection and characterization of pancreatic lesions on CT imaging.
This position also includes a leadership role in mentoring junior researchers and onboarding new team members, helping maintain the collaborative, inclusive, and high-performing culture of the lab.
Key Responsibilities:
• Oversee clinical data collection, de-identification, and organization of a large patient imaging cohort using REDCap and secure data systems.
• Perform manual image segmentation and curate CT imaging datasets for radiomics analysis.
• Collaborate with AI/ML engineers, postdocs, and radiologists to train, evaluate, and refine models for tumor detection and classification.
• Coordinate cross-departmental efforts, including pathology correlations and multidisciplinary team meetings.
• Lead and co-author research manuscripts, abstracts, and grant applications.
• Mentor postdoctoral fellows and lead onboarding and training efforts for new team members.
Qualifications
Qualifications:
• MD or PhD in Radiology, Medical Imaging, Biomedical Engineering, Data Science, or related field.
• Demonstrated experience in clinical research and medical imaging (CT preferred).
• Strong data management skills and experience with REDCap, Excel, and SQL.
• Background in radiomics, machine learning, or medical AI is highly desirable.
• Excellent communication and leadership skills, with experience guiding junior researchers.
Preferred Qualifications:
• Experience in abdominal imaging.
• Familiarity with AI model evaluation and data harmonization techniques.
• Previous publications or abstracts in radiology or AI-focused research.
Why Join Us?
You'll be part of a mission-driven team developing AI solutions to address one of the deadliest cancers. Our lab is highly collaborative, internationally diverse, and actively engaged in cuttingedge research supported by strong institutional and external partnerships (e.g., Microsoft, Lustgarten Foundation). You'll also play a central role in building and supporting a growing team

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