Postdoctoral Fellow in Computational Biology

At Moffitt Cancer Center, we strive to be the leader in understanding the complexity of cancer and applying these insights to contribute to the prevention and cure of cancer. Our diverse team of over 9,000 are dedicated to serving our patients and creating a workspace where every individual is recognized and appreciated. For this reason, Moffitt has been recognized on the 2023 Forbes list of America’s Best Large Employers and America’s Best Employers for Women, Computerworld magazine’s list of 100 Best Places to Work in Information Technology, DiversityInc Top Hospitals & Health Systems and continually named one of the Tampa Bay Time’s Top Workplace. Additionally, Moffitt is proud to have earned the prestigious Magnet® designation in recognition of its nursing excellence. Moffitt is a National Cancer Institute-designated Comprehensive Cancer Center based in Florida, and the leading cancer hospital in both Florida and the Southeast. We are a top 10 nationally ranked cancer center by Newsweek and have been nationally ranked by U.S. News & World Report since 1999.
Working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer. Join our committed team and help shape the future we envision.

Summary

Postdoctoral Fellow in Computational Biology

Tumor evolution proceeds at a rapid pace. Drug development does not. In order for cancer therapy to achieve a durable response over years rather than months, it must “evolve” as quickly as the tumor does. In contrast to a cell’s DNA, its RNA – the transcriptome – is a highly dynamic machinery which operates within ranges, orders of magnitudes wider than those of the genome. Its role in shaping clonal evolution and implementing a cell’s response to its environment is undoubted, yet nowhere close to understood. We seek applications from a computer scientist with a Ph.D. and strong background in machine learning to develop a new class of temporal biomarkers of cell fitness using supervised machine learning approaches.

Position Highlights:

• We develop software solutions that enable data-driven, clinical, decision-making by providing oncologists and specialized tumor-boards with patient-specific genomic information. Executing this mission will rely on a long-term synergy between various evolving perspectives on tumor populations and on an interdisciplinary effort to sharpen these perspectives.

The Ideal Candidate:

• In-depth familiarity with OO programing concepts and 10+ years of experience using them.
• Experience with 3D and 2D live-cell imaging: cell segmentation and cell tracking.
• Experience with machine learning approaches, especially supervised methods such as Bayesian MKL, deep neural networks (Bayesian neural nets, LSTM, convolutional) is required. Experience with PyTorch or TensorFlow is also needed. Prior work with very large datasets, such as CIFAR-10 and imaging data pre-processing is preferred but not required.
• Experience with analysis and interpretation of scRNA-, scDNA-seq, MRI images, H&E images is also a plus. 

Responsibilities:

• Successful candidate will work with a powerful combination of single-cell RNA sequencing data and live-cell imaging to learn various aspects about a clone’s fitness from its transcriptome.

Credentials and Qualifications:

• Ph.D. in computer science, computational biology, or related field

How to Apply: Please send your CV and cover letter to noemi.andor@moffitt.org