Machine Learning and Imaging Analytics Postdoctoral Fellow
- H. Lee Moffitt Cancer Center
- Location: Tampa, FL
- Job Number: 7072778 (Ref #: hlj_28268)
- Posting Date: Dec 3, 2020
- Application Deadline: Open Until Filled
Job DescriptionDr. Issam El Naqa seeks to hire a Postdoc to join his lab. The specific project will involve application of advanced machine learning and artificial intelligence to interrogate and integrate imaging and other information (from radiomics to panomics) for predicting response to cancer treatment. The imaging information consist of diagnostic imaging (CT, MRI, PET) in addition to new imaging information acquired during radiotherapy treatment (optical and acoustic imaging).
To learn more about the department, visit Department of Machine Learning.
• 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 medical image analysis, image-guidance and adaptation, distributed machine learning, dynamic decision support, and computational modeling of treatment outcomes.
• Moffitt integrates excellent patient care with cutting-edge clinical and basic research. Having a cancer hospital on-site provides unique opportunities for translational research.
• Outstanding mentorship from expert faculty with wide-ranging funded research programs including T32 Training Grants.
• You will be encouraged and supported to apply for training grants.
The Ideal Candidate:
• Medical image analysis and/or computer vision knowledge.
• Familiarity with conventional machine and deep learning algorithms.
• Good computing and programming skills are important for this position preferably in Matlab, Python or C/C++.
• Develop new algorithms for deep learning with imaging information for predicting and adapting decision making for diagnostic and prognostic radiomics/panomics 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 Medical Physics, Physics, Electrical or Biomedical Engineering, Computer Science, or related discipline is required.
• Should have at least one first Author publication.
You will be eligible for benefits offered to our Team Members – Medical, Dental, Vision, Paid Time Off, Retirement, Parental Leave and more. With a move to Tampa, you may be eligible for relocation allowance. Reason to relocate, aside from the sunshine, beaches and year-round outdoor recreation associated with the Gulf Coast of Florida, Tampa is a thriving metropolitan city with unique cultural attractions, low cost of living and a high quality of life. We strive for work/life balance.
If you have the vision, passion, and dedication to contribute to our mission,
then we have a place for you.
Interest applications should apply to the opportunity by clicking the link for Machine Learning and Imaging Analystics Postdoc Fellow opportunity. To be considered, please be sure to attached a single PDF file that includes a cover letter summarizing your research training and accomplishments, a personal statement of scientific interests and goals, current CV with recent publications, and contract information for three references. If you have questions, please feel free to contact Dr. Issam El Naqa via email at Issam.ElNaqa@Moffitt.org.
Mission To create a Moffitt culture of diversity and inclusion as we strive to contribute to the prevention and cure of cancer. Vision Moffitt Cancer Center is recognized as the model wherein the diversity of our employees and communities is valued and supported as essential components to contributing to the prevention and cure of cancer. The cancer center is an equal opportunity employer. It is the policy of the cancer center to prohibit unlawful discrimination and harassment of any type and to afford equal employment opportunities to workforce members and applicants, regardless of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, disability, genetic information, veteran’s status or any other characteristic protected by federal, state or local law.