"Research Associate - FELIX Lab 2.0"

General Description

Salary: $62,232 - $62,232 a year

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