Senior Scientist - In Vivo Pharmacology
Based in Menlo Park, CA since 2018, Zai Lab U.S. is focused on discovering and developing novel therapies for the treatment of cancer and inflammatory diseases. We are an innovative, research-based, commercial stage company, with over 1,600 employees worldwide and a diversified and strong pipeline poised for continued growth. This is an exciting time for us as we build our R&D Drug Discovery team and advance our global pipeline, aiming to produce 1-2 global INDs per year.
At Zai (NSDAQ: ZLAB), we are working to generate optimum therapeutics for significant diseases affecting peoples throughout the world. Transforming lives of patients by identifying new and smarter ways to treat and cure disease is our mission. We bring together the best minds from all over the world to pursue our goals.
As part of the In Vivo Pharmacology team in Menlo Park, the successful candidate will be responsible for developing, planning, and performing animal studies using human and mouse cell lines and performing ex vivo analyses to support discovery and development of new therapeutics in oncology and immuno-oncology.
Major Responsibilities and Duties:
- Design in vivo studies to support the goals of oncology and/or immune-oncology projects. Includes in-house and out-sourced in vivo studies in mice.
- Perform xenograft and syngeneic tumor studies to test efficacy, pharmacology, and mechanism of action of anticancer therapeutics. Hands-on work will include developing and optimizing xenograft and syngeneic tumor models, intravenous, intraperitoneal, and intragastric dosing of mice, and isolation and processing of mouse blood and tissue.
- Support the development of new in vivo models. May include, but is not limited to, humanized mouse models, the use of bioluminescent imaging, and in vivo models of target discovery
- Ability to perform in vitro and ex vivo work to examine drug pharmacodynamics and mechanisms of action, including: 1) Multi-color flow cytometry to examine tumor infiltrating immune cells. 2) Assays to examine target binding and downstream pathway modulation, including phosphoprotein and cytokine analyses. 3) Cell-based assays, including viability, cytotoxicity, and proliferation of cancer cells and activation and cytotoxicity of immune cells
- Analyze and present data as a key member of project teams representing the In Vivo Pharmacology department.
- Work collaboratively with other departments on multiple projects concurrently and coordinate activities across functions.
- PhD with at least 3-5 years of post-doctorate experience or MS with 8-10 years of experience.
- At least 3-5 years of hands-on in vivo experience designing and running in vivo models of oncology and/or immuno-oncology is required.
- Expertise in handling and dosing mice, including intravenous, intraperitoneal, and intragastric administration, and mouse tissue and blood collection is essential.
- Experience with animal models of auto-immunity and/or inflammation is a plus.
- Hands-on experience with various in vitro laboratory techniques, including multi-color flow cytometry, Western blot, qRT-PCR, ELISA, and immunohistochemistry is strongly preferred.
- Capable of working independently in a fast-paced, team-oriented environment, demonstrating multitasking capabilities.
- Excellent experimental design, troubleshooting, and data analysis skills are required.
- Great communication skills and team spirit is a must; ability to communicate results within Pharmacology and Biology teams and at project team meetings required.
- Previous industry experience is a preferred.
Disclaimer: This description is not intended to be construed as an exhaustive list of duties, responsibilities, or requirement for the position. All personnel may be required to perform duties outside of their normal responsibilities from time to time, as needed.
All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or based on disability.