Position Highlights:

• The position offers a unique opportunity to work in a world-class research environment, with state-of-the-art facilities and with strong collaboration with many researchers and clinicians from diverse fields.
• It also offers exciting opportunities that include but not limited to developing new algorithms for molecular data (genomics, transcriptomics, etc.), medical image analysis (radiomics, pathomics), image-guidance and adaptation, federated machine learning, dynamic decision support, and computational modeling of treatment outcomes.
• Moffitt integrates excellent patient care with cutting-edge clinical and basic research and wealth data for machine learning applications. Having a cancer hospital on-site provides unique opportunities for translational research.
• Outstanding mentorship from expert faculty with wide-ranging funded research programs from NIH and DoD including T32 Training Grants.
• You will be encouraged and supported to apply for training grants and pursue IP applications.

The Ideal Candidate:

• Genomics, Medical image analysis and/or pattern recognition knowledge.
• Familiarity with conventional machine and deep learning algorithms.
• Good computing and programming skills are important for this position preferably in Python MATLAB, R, or C/C++.

Responsibilities:

• Develop new algorithms for deep learning with integrated genomics and imaging information for predicting and adapting decision making for diagnostic and prognostic applications in cancer.
• Collaborate with team members on developing new tools for optimal dynamic decision support applications, manuscript writing, and generating data for grant applications.

Credentials and Qualifications:

• A PhD or equivalent degree in Computer Science, Medical Physics, Physics, Electrical or Biomedical Engineering, or related discipline is required.
• Should have at least one first author publication.