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The Swanson Lab at Cedars-Sinai Medical Center, Department of Neurosurgery is looking for a Postdoctoral Scientist to join the team!

Are you ready to be a part of breakthrough research?

Mathematical neuro-oncology is an exciting interdisciplinary field incorporating applied mathematics, artificial intelligence, clinical oncology, cancer biology, radiology, pathology and informatics. This field represents a major new way of thinking in the generation of practical clinical tools to benefit people diagnosed with brain tumors.

Kristin R. Swanson, Ph.D., and her research team in the Mathematical Neuro-Oncology Lab at Cedars-Sinai are at the forefront of this field developing numerous models of glioma tumors. Dr. Swanson and her team are finding ways to make these models specific for predicting and simulating individualized tumor behavior under different treatment scenarios. Dr. Swanson's research team's current projects focus on growing and harnessing these resources to predict patient-specific tumor growth, find patient-specific markers of tumor progression and identify predictors of response to therapy in individuals.

Possible research focuses include:

• Model implementation and comparison with experimental and/or clinical data
• Determining the impact of tumor location on outcomes
• Quantifying extent of tumor cell invasion and proliferation in individual patients
• Understanding how tumor processes manifest on MRI
• Contributing ideas for database development/data management.

The ideal candidate should have a strong mathematical/computational background with experience in biological applications. Experience with the analysis of omics, imaging, clinical and other biomedical data is desired. Experience with computer programming is strongly preferred (R, Python and/or MatLab), while familiarity with computational methods for solving partial differential equations would also be beneficial. The candidate should have experience working in an interdisciplinary environment with the ability to present technical results to audiences from different disciplines and backgrounds. The candidate will be expected to contribute to achieving research grant goals and objectives as well as securing new sources of funding (not required to generate independent funding). Depending on experience, the candidate may supervise junior scientists, engineers or technicians on assigned work, mentor/train staff in development of technical, project development skills, as well as provide input into staffing of overall project teams. See our website to learn more about the developing field of Mathematical Neuro-Oncology http://MathematicalNeuroOncology.org.

Working independently but in close cooperation with the Principal Investigator, Dr. Kristin Swanson, and other Research Scientists, the Postdoctoral Scientist will perform routine and complex mathematical modeling, machine learning, AI, computational, and statistical procedures to answer a variety of questions focused on direct clinical applications of mathematical modeling.

Primary Job Duties and Responsibilities:

• May assist in the preparation of grant proposals, but is not responsible for generating grant funds.
• May participate in publications and presentations as author or co-author.
• Designs and performs experiments. Will keep appropriate experimental records and documentation and analyze the results with the Principal Investigator.
• Analyzes interpret, summarizes, and compiles data.
• Operates and maintains equipment and instruments.
• May observe MD-patient or MD-human research subject interactions as they pertain directly to research being performed.

Education:

• Doctorate (MD, PhD, VMD, or DDS) in the area directly related to the field of research specialization.

Experience and Skills:

• Acquires technical and theoretical knowledge of research project and objectives during one to five (1-5) year post-doctoral appointment.
• Works independently on research projects designed by a mentor (typically the PI) within area of specialization.
• Demonstrated aptitude to perform experimental protocols and procedures, including detailed data collection, analysis, operation, and maintenance of specialized equipment.
• Knowledge of safety standards and maintenance of specialized equipment.