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Location
South San Francisco, CA, United States
Posted on
Mar 02, 2022
Profile
The Opportunity
The heart of insitro’s strategy is the development of novel, cutting edge methods in machine learning and high-throughput biology to address key bottlenecks in the drug development pipeline. In alignment with this strategy, the Advanced Cellular Technology Group is building the foundational platforms for performing high-throughput genetic and phenotypic screens. As an associate scientist, you will work with a dynamic team to help develop cutting edge functional genomic tools using CRISPRn/a/i and other genome editors, state-of-the-art gene delivery techniques, next-generation sequencing, and image phenotyping to model human diseases and discover drugs. We are looking for motivated and talented candidates who are interested in being part of a unique, cross-disciplinary team of biologists, bioengineers, machine learners, and data scientists who want to make a difference.
You will be joining as the founding team of a biotech startup that has long-term stability due to significant funding, yet is very much in formation providing many opportunities for significant impact. You will work closely with a very talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us and help make a difference to patients!
About You
- B.S./M.S./Ph.D. in biological science with preference for genetics and/or genomics background, bioengineering or relevant disciplines, or equivalent experience
- 2-3 years of relevant research experience, in academia or industry
- Strong experience with mammalian cell culture required. Ideally, experience with human induced pluripotent stem cell culture (iPSC)
- Experience with CRISPR-Cas9/cloning/NGS and molecular biology techniques
- Exposure to characterizing mammalian cell cultures via FACS, transcriptomics, or fluorescence imaging modalities
- Excellent lab practice, detail oriented, and strong communication skills
- Ability to work independently and collaboratively as part of a dynamic team
- Highly motivated, eager to learn
Nice to Have
- Experience in NGS data analysis and bioinformatic tools
- Familiarity with iPSC differentiation and assay development
Benefits at insitro
- Excellent medical, dental, and vision coverage; insitro pays 100% of premiums for employees
- Excellent mental health and well-being support
- Open vacation policy
- Access to free onsite baristas and cafe with daily lunch and breakfast
- Access to free onsite fitness center
- Commuter benefits
- Paid parental leave
- Competitive pay and 401(k) matching
- Flexible work schedule (on site and remote)
About insitro
insitro is a data-driven drug discovery and development company using machine learning and data at scale to transform the way that drugs are discovered and developed for patients. insitro is developing predictive machine learning models to discover underlying biologic state based on human cohort data and in-house generated cellular data at scale. These predictive models can be brought to bear on key bottlenecks in pharmaceutical R&D to advance novel targets and patient biomarkers, design therapeutics, and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of biologic insights and molecules in neuroscience and metabolic diseases. Since formation in mid 2018, insitro has raised over $700 million from top tech, biotech, and crossover investors and from collaborations with pharmaceutical partners. For more information on insitro, please visit the company’s website at ****rel=no-follow>****/>,datePosted:2022-03-03T01:39:54 00:00,validThrough:2022-04-02T03:59:59 00:00,employmentType:FULL_TIME,hiringOrganization:{name:**MEMBERS ONLY**SIGN UP NOW***.,@id:2304408,url:****San Francisco, CA,address:{addressCountry:US,addressLocality:California,addressRegion:California,postalCode:94080,@type:PostalAddress},@type:place},industry:Science/R&D, Biotechnology, Genetics,workHours:Full time,educationRequirements:Doctorate/PHD/MD,@type:JobPosting,@context:****
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