Sriram Lab – Junior/Assistant/Associate/Full Specialist
Application Window
Open date: November 12, 2024
Next review date: Wednesday, Nov 27, 2024 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.
Final date: Tuesday, May 12, 2026 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
Position description
Sriram Lab – Junior/Assistant/Associate/Full Specialist
The Sriram Lab is seeking a Junior, Assistant, Associate, or Full Specialist. The specialist will be involved in development of hyperpolarized 13C MR markers using dissolution dynamic nuclear polarization (DNP) technology of tumor metabolism in the translational metabolic imaging laboratory of Dr. Renuka Sriram. (https://radiology.ucsf.edu/research/labs/translational-metabolic-imaging). The breadth of studies will encompass the chemical preparation of promising precursors and its testing in ex vivo models, validation in cutting edge preclinical models of urologic cancer. The studies will utilize living cells in bioreactors, patient derived tissue slices as well as mouse models. These biologically relevant animal models will be used to identify and validate imaging markers of disease presence, severity, and treatment response.
Another dimension of this project involves computational proficiency with data analysis kinetic modeling as well as multi-omics integration.
Required Qualifications:
- Specialists appointed at the Junior rank must possess a baccalaureate degree in a related science (or equivalent degree) or at least four years of research experience.
- Specialists appointed at the Assistant rank must possess a master’s degree (or equivalent degree) or a baccalaureate degree (or equivalent degree) with three or more years of research experience.
- Specialists appointed at the Associate rank must possess a master’s degree (or equivalent degree) or five to ten years of research experience.
- Specialists appointed at the Full rank must possess a terminal degree (or equivalent degree) or ten or more years of research experience.
- Knowledge and experience with magnetic resonance imaging (MRI) or spectroscopy (MRS) technology.
- Applicants must meet all the qualifications by the time of hire.
- Applicant materials must list current and/or pending qualifications upon submission.
Preferred Qualifications:
- Ability to work with mouse models
- Candidates with a hyperpolarized 13C MRI or other MRI based metabolic imaging background -Candidates with fervent interest in metabolism and its implication in diseases like cancer are encouraged to apply
- Familiarity with computational tools (e.g. MATLAB, Linux, Python, R, PRISM)
- Hands-on experience of mouse tumor models
- Familiarity with biochemical and molecular assays
See Table 24B for the salary range for this position. A reasonable estimate for this position is $53,100-$188,200.
Please apply online at: https://aprecruit.ucsf.edu/JPF05376 with a cover letter and CV.
Application Requirements
Cover Letter
Curriculum Vitae - CV must clearly list current and/or pending qualifications (e.g. board eligibility/certification, medical licensure, etc.).
Statement of Research (Optional)
Statement of Contributions to Diversity - Please see the following page for more details: Contributions to Diversity Statement
(Optional)Misc / Additional (Optional)
About UC San Francisco
As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.
UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.