Research Assistant (1/2)

The Research Assistant (Staff Research Associate I) position is in a highly dynamic research lab focused on understanding the molecular and immunological mechanisms that establish maternal–fetal immune tolerance and how these mechanisms are altered in pregnancy complications.

The incumbent at the entry level (SRA 1) will perform research experiments under the direction and training of the Principal Investigator and senior laboratory members. Research in the laboratory combines biochemistry, protein engineering, immunology, and experimental models to investigate antibody–antigen interactions and mechanisms of immune tolerance. Approaches may include programmable protein display, molecular cloning, recombinant protein and antibody expression and purification, biochemical and cell-based assays, next-generation sequencing, flow cytometry, and mouse models of pregnancy and immunity. These approaches reflect the lab's broader experimental program, which combines antigen discovery with molecular characterization of antibody–antigen recognition.

The incumbent will initially receive training in relevant laboratory techniques and, with increasing proficiency, will take on greater responsibility for independent experiments and research projects. Responsibilities will include experimental planning and execution, data collection and analysis, maintenance of detailed laboratory records, and presentation of research progress at laboratory meetings. The incumbent will be responsible for presenting the research progress every 3 months.

The incumbent shall be flexible and conform to irregular work hours that may be needed of Lab for work 24/7 (weekends, holidays and so on). If needed, the incumbent will act as liaison between the research team and the clinical staff. If needed, he/she will collect placenta tissue from various sites in San Francisco and to prepare the tissue for experiments.

Additional duties include preparation of buffers and reagents, maintenance of laboratory stocks and experimental animals, assistance with laboratory equipment and organization, and other research-related duties as assigned by the PI and senior laboratory personnel.

DEPARTMENT INFORMATION:

The Department of Obstetrics, Gynecology and Reproductive Sciences (Ob, Gyn & RS) is a major academic Department in the School of Medicine, engaged in clinical, research and training activities at the Parnassus, Mount Zion, and Zuckerberg San Francisco General Hospital campuses, the new Betty Irene Moore Women’s Hospital at Mission Bay, as well as satellite locations throughout the Bay Area, with an annual operating budget of $150 million. The Department has 134 full-time faculty, 117 other academic appointees, 13 post-doctoral fellows, 22 clinical fellows, 32 residents, 138 voluntary clinical faculty and 270 staff.

The mission of the Department of Obstetrics, Gynecology & Reproductive Sciences is to improve the lives and health of all women through excellence, innovation and leadership in patient care, scientific discovery, education, advocacy, and diversity, equity and inclusion. We are committed to providing quality health care services; educating health care providers and investigators; and conducting research to advance knowledge in our field.

Reasonable accommodation(s) to qualified individuals with disabilities are available as part of the application and interview processes. If you would like to request accommodations, please contact the recruiter or hiring manager. If workplace accommodations are needed after a job offer is made, please contact the supervisor and/or Disability Management Services (DMS) at View phone number on aiapply.co to initiate the interactive process.

Responsibilities

Qualifications

REQUIRED:

• BA/BS in a related science and knowledge of, or experience with, the basic techniques or methods required by the position; and/or an equivalent combination of education and experience.
• Proficiency in MS Office suite
• Ability to work independently as well as work in a team
• Self-motivated and organized
  
  

PREFFERED:

• Experience/proficiency with coding languages such as python and/or R