Faculty: Pioneering Cancer Early-Detection & Interception

Mayo Clinic

Phoenix (AZ)

On-site

USD 250,000 - 350,000

Full time

14 days+
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Benefits offered by this job

Competitive startup package
Access to AI platforms
National research network

Job summary

Mayo Clinic invites applications for open-rank faculty positions in Early-Detection and Interception with leadership potential. The roles span Phoenix/Scottsdale, AZ and Rochester, MN, integrating discovery, translational science, clinical care, and advanced analytics to redefine early cancer detection.

Strong collaboration across AI, genomics, and population health is expected. Ideal candidates will lead large longitudinal cohorts, drive clinical-grade genomic initiatives, and expand access to

Qualifications

  • Qualified candidates must hold a doctoral degree (M.D., Ph.D., or equivalent).
  • Board-certified or board-eligible in Medical Oncology, Hematology/Oncology, or related field is desirable.

Responsibilities

  • Design and lead prospective cohorts of healthy individuals and high-risk populations.
  • Integrate clinical, genomic, and longitudinal health data for early detection and interception.
  • Lead translational science programs focused on early detection and interception.
  • Partner with Mayo Clinic Platform and AI programs to implement predictive analytics.
  • Develop strategies to translate discoveries into clinical trials and care pathways.
  • Expand access to innovative trials and precision medicine across diverse settings.

Skills

Leadership
Clinical/Translational research
Data integration
Collaborations
Funding track record

Education

Doctoral degree in genetics, molecular biology, immunology or related field

Job description

Mayo Clinic invites applications for open-rank faculty positions in Early-Detection and Interception with leadership potential. The roles span Phoenix/Scottsdale, AZ and Rochester, MN, integrating discovery, translational science, clinical care, and advanced analytics to redefine early cancer detection.

Strong collaboration across AI, genomics, and population health is expected. Ideal candidates will lead large longitudinal cohorts, drive clinical-grade genomic initiatives, and expand access to

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