The Emamaullee Transplant Immunology Lab in the Department of Surgery at the University of Southern California is looking for a Statistician I to join our team. You will join an interdisciplinary team dedicated to transforming our understanding of transplant immunology and clinical outcomes by providing cutting-edge solutions for the analysis of biomedical data.
You will work directly with Dr Emamaullee’s team and outside partners on a variety of projects, tackling among the most significant challenges facing human health. Our projects are diverse and highly translational, using large national datasets, computational biology techniques including single cell transcriptomics, and machine learning regression modelling of disease. Members of our research group collaborate in highly interdisciplinary teams throughout a project’s lifecycle: from the initial design phase to the study publication, data release, and subsequent monitoring of the outcomes. This is a uniquely exciting time to join our team to make a significant impact on the life and well-being of organ transplant recipients, including both adults and children.
Environment and background
The Emamaullee Lab has received support from the National Cancer Institute, National Cancer Institute, Children’s Hospital Los Angeles, the American Society of Transplantation, and the Children’s Heart Foundation. Our research focuses on the application of single cell multiomics, mathematical modeling, integrating clinical trials, pre-clinical studies and molecularly targeted therapy, which focuses on molecular and cellular changes specific to transplant rejection.
The University of Southern California (USC), founded in 1880, is located in the heart of downtown L.A. and is the largest private employer in the City of Los Angeles. As an employee of USC, you will be a part of a world-class research university and a member of the "Trojan Family," which is comprised of the faculty, students and staff that make the university what it is.
Position responsibilities
We are seeking a talented statistician/data scientist with a strong interest in human biology and expertise in the statistical analysis of biological data. The candidate will interact frequently with lab members and clinicians to understand their experiments, data, and project goals. The ability to communicate effectively with biologists and clinicians on their own terms is essential. The successful applicant will be capable of designing experiments, providing compelling data visualizations, and applying appropriate statistical analyses of experimental data. Data sets may include high-dimensional multi-omic data and complex clinical data from electronic medical records. Contributions will also be made to current and future development of grant applications, scientific research, and scientific manuscripts for the group.
Qualifications
Demonstrable Personal Attributes:
Knowledge and Skills
Education and Experience:
Masters or PhD in statistics, biostatistics, quantitative sciences (physics, or applied mathematics) or engineering (electrical engineering, computer science, industrial engineering).
Three or more years’ experience in hands-on statistical data analysis, ideally in the life sciences
The annual base salary range for this position is $85,379.61 - $90,000. When extending an offer of employment, the University of Southern California considers factors such as (but no limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations
USC will consider for employment all qualified applicants with criminal records in a manner consistent with applicable laws and regulations, including the Los Angeles County Fair Chance Ordinance for employers and the Fair Chance Initiative for Hiring Ordinance, and with due consideration for patient and student safety. Please refer to the Background Screening Policy Appendix D for specific employment screen implications for the position for which you are applying.
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