Postdoctoral Fellow Machine Learning Genome Mutability Organization Molecular Interactions

At Moffitt Cancer Center, we come face-to-face with cancer every day, but we also see courage. And it inspires us to be the safest and best place for cancer care – to bring greater hope to every patient we serve. It’s why we’ve been continually named One of the Top Places to Work in the Tampa Bay Area. As the only National Cancer Institute-designated Comprehensive Cancer Center based in Florida, Moffitt employs some of the best and brightest minds from around the world. Moffitt is the leading cancer hospital in both Florida and the Southeast and has been nationally ranked by U.S. News & World Report since 1999. Because working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer. Join a dedicated, diverse and inclusive team of over 7,000 to be a part of the Courageous future we envision.

Summary

We seek a creative and motivated postdoctoral researcher with background in structural biology and machine learning to join the team of Dr. Aleksandra Karolak. Our current projects focus on the role of DNA or proteins molecular structure and sequence on the mutagenesis, chromatin architecture, tumor topology in cancer; furthermore, we are involved in identification and design of novel therapeutics. If your background overlaps and if you are interested in one of the projects focusing on 1) understanding the impact of DNA damage and repair on highly heterogeneous patterns of mutations, responses to treatment, genome conformation, and/or tumor topology, metabolic reprogramming across the genomes and populations, or 2) molecular interactions (protein-protein, protein-DNA, protein-small molecules) and identification of novel compounds to treat cancer – we encourage you to apply. We have exciting opportunities for you within our team at the institution that will strongly support your scientific growth and future successes.

The Computational Oncology Group in the Machine Learning Department at Moffitt combines multidisciplinary and multiscale approaches from the fields of chemistry, structural biology, machine learning, information theory, and mathematical oncology, to advance cancer research. We collaborate with the departments of gastrointestinal oncology and molecular medicine/drug discovery. We also actively collaborate with the extramural oncology centers and academic institutions.

To learn more about the exciting work being done visit: http://lab.moffitt.org/KAROLAK

Position Highlights:

• Moffitt integrates excellent patient care with cutting-edge clinical and basic research. Having a cancer hospital on-site provides unique opportunities for translational research.
• The position is essential for development of comprehensive tools benefiting basic to clinical research through 1) identification of novel approaches and biomarkers to treat cancer, and 2) through the improved stratification of cancer patients.
• The position offers vibrant and interactive work environment in the Quantitative Science Division and results will bring value beyond the community of Moffitt patients.
• 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:

• High motivation and desire to be part of multidisciplinary group, good work ethic.
• Excellent interpersonal and communication skills (written and verbal).
• Documented experience with machine learning concepts, tools, and applications.
• High proficiency with at least one of the programming languages and statistical packages.
• Deep knowledge of biological data sources and databases.
• Documented experience with concepts and applications from structural biology of proteins and/or DNA.
• Preferable knowledge of cancer biology.
• Experience with extraction, handling, and processing of large data sets.

Responsibilities:

• Data preparation, organization, and analysis.
• Development of new and tuning of existing models and analytical approaches.
• Presentation of data and results in a clear and concise manner.
• Active participation in the group meetings and meetings with the collaborating teams.
• Ability to work with the team and independently.
• Supervision of undergraduate and graduate students.
• Preparation of grant applications, publications, and presentations.
• Meeting project goals.

Credentials and Qualifications:

• Ph.D. degree and research experience in the fields of machine learning, computer science in biomedical applications or related field of study.
• At least one first-author publication.