Oni-Orisan Lab – Assistant Specialist – Computational Lab Part-time

Oni-Orisan Lab – Assistant Specialist – Computational Lab

The Oni-Orisan Lab at UCSF's Department of Clinical Pharmacy has two major interests that fall within our overarching research mission. First, we aim to establish pharmacogenetic predictors of statin efficacy and safety. Second, we aim to advance pharmacogenomic discovery and validation in historically excluded populations.

We seek to hire an assistant specialist to assist our team in generating, managing, and analyzing large datasets containing electronic health records, genomic data, drug regimens, and clinical outcomes.

Responsibilities include generating drug response phenotypes (e.g., developing the genotype /phenotype), constructing longitudinal data sets for further analyses, generating visualization plots to characterize the data, conducting inferential statistics, and preparing/analyzing all requested data analytics, as well as archiving code for future use. Through this work, we expect that our specialist will play an integral role in advancing our knowledge of pharmacogenomics. We are seeking an individual with a 12-month commitment. The successful candidate will have experience in precision medicine, cardiology, and/or pharmacogenomics, and experience in statistical analyses working with large datasets containing electronic health records.

Appointees in the Specialist series will be expected to engage in specialized research and professional activities, but do not have teaching responsibilities. Specialists are expected to use their professional expertise to make scientific and scholarly contributions and may participate in University and Public Service.

Required Qualifications

• MA/MS (or equivalent degree) or a bachelor's degree in Health Data Science with three or more years of research experience.
• One year of experience in a research setting (can be during educational activities).
• Proficiency in statistics, data analysis, research methods, and statistical packages such as SPSS, SAS, and/or R, or a related package.
• Prior experience constructing complex, longitudinal data sets, conducting inferential statistics, and related coding.
• Knowledge of large dataset management, data analysis, and data visualization.
• Existing experience in statistical analyses working with large datasets containing electronic health records, genomic data, drug regimens, and clinical outcomes.
• Existing training/experience in biostatistics, pharmacogenomics, cardiology, and precision medicine.
• Ability to effectively manage time and see assigned parts of projects through to completion on deadline.
• Skills to communicate complex information in a clear and concise manner, both verbally and in writing.
• Excellent verbal and written communication and presentation skills; excellent organizational skills; and excellent interpersonal skills to work effectively in a diverse team
• At least one peer-reviewed publication or submitted publication under review.
• Self-motivated, positive attitude, strong attention to detail
• Ability to work standard Monday to Friday, normal business hours.
• Ability to work on-site at least 3 days (Tuesday, Wednesday, and Thursday) per week.

Preferred Qualifications

• MA/MS degree (or equivalent degree)

Screening of applicants will begin immediately and will continue as needed throughout the recruitment period. For full consideration, please apply by the initial review date. Salary will be commensurate with the applicant's experience and training.

See Table 24B for the salary range for this position. A reasonable estimate for this position is $63,500-$70,700.

Please apply online at [Please click the Apply button for the link or address], with CV and contact information for two references. Applicant materials must list current and/or pending qualifications upon submission. The selected candidate must meet all of the qualifications at the time of appointment.

Document requirements

• Curriculum Vitae – CV must clearly list current and/or pending qualifications (e.g. degree status, etc.).
• Cover Letter (Optional)
• Statement of Research (Optional)

Reference requirements

• 2 required (contact information only)

Location: San Francisco, CA