Clinical Postdoctoral Fellow to carry out the following research activities.

-Retrospective review of the clinical and biological characteristics of GU cancer patients and corresponding therapeutics to correlate with clinical outcomes including clinical response and survival.

-Collaborating with other scientists into study mechanisms of response and resistance to immunotherapy, targeted therapy, and chemotherapy in GU cancers.

-Correlate biological mechanisms of GU cancers with clinical outcomes of patients with GU cancers.

Successful candidates must have strong clinical oncology background and have experiences working on clinical data collection on patient and tumor characteristics. Candidates must have basic understanding and experiences on studying resistance mechanism of immune checkpoint blockade therapy in malignancies. Successful candidate must be able to design novel projects, create hypothesis driven research plan, maintain excellent descriptions of data collected, standardize, and validate new methods and be able to interpret results. Computer skills such as entering research data into graphic and statistics programs as well as the generation of figures are essentials. The employee should provide scientific expertise and organizational skills in getting involved in various research projects involving human subject research and correlation with pre-clinical data. Will be responsible for clinical data collection, analysis, summary, interpretation, and coordinating research procedures with collaborators including statisticians and basic research scientists.

LEARNING OBJECTIVES

-Understanding the clinical and biological characteristics of GU cancer patients and corresponding therapeutics in correlation with clinical outcomes.

-Identification of mechanisms of response and resistance to immunotherapy, targeted therapy, and chemotherapy in GU cancers.

-Identification of biological mechanisms specific to GU cancers to guide therapeutic development.

-Build knowledge in personalized medicine and precision health.

-Gain experience in collaborating with experimental biologists to design and execute correlative analyses that address biological questions.

-Develop proficiency in scientific writing and communication, including publishing in peer-reviewed journals and presenting research at conferences.

-Obtain grant writing skills.

ELIGIBILITY REQUIREMENTS

M.D.

ADDITIONAL APPLICATION INFORMATION

Prefer a candidate with the following qualifications/experience:

• Recent (within 3 years) graduate

• An understanding of cancer biology

• Background in clinical oncology and hematology

• An understanding basic statistics and mathematics

• Ability to collaborate with clinical investigators and experimental biologists to design and execute bioinformatics analyses that address clinical and biological questions.

• Strong written and verbal communication skills, including the ability to publish in peer-reviewed journals and present research at conferences.

POSITION INFORMATION

MD Anderson follows the NIH stipend levels as outlined by the Kirchstein - NRSA (https://grants.nih.gov/grants/guide/notice-files/NOT-OD-23-076.html) . This full-time trainee position will provide a salary between $56,484 to $68,604, dependent upon the years of postgraduate experience.

MD Anderson offers compensated trainees:

• Paid medical benefits (zero premium) starting on first day for trainees who work 30 or more hours per week

• Group Dental, Vision, Life, AD&D and Disability coverage

• Paid Education Vacation and Sick Leave

• Paid institutional holidays, wellness leave, childcare leave and other paid leave programs

• Teachers Retirement System defined-benefit pension plan and two voluntary retirement plans

• Employer paid life, AD&D and an illness-related reduced salary pay program

• Health Savings Account and Dependent Care Reimbursement flexible spending accounts

• Fertility benefits

• State of Texas longevity pay

• Extensive wellness, fitness, employee health programs and employee resource groups

FACULTY MENTOR

To accomplish the learning objective, the candidate will be matched with Drs. Jianjun Gao and Arlene Siefker-Radtke