(Associate) Scientist, Flow Cytometry Specialist

Translational Science · South San Francisco, California
Department Translational Science
Employment Type Full-Time

The Opportunity

The heart of insitro’s strategy is the development of novel, cutting edge methods in machine learning and high-throughput biology that address key bottlenecks in the drug development pipeline. To accomplish that, we are putting together a team of life scientists with cutting-edge cellular and technological expertise. In this role, you will lead projects focused on flow-based phenotyping and cell sorting within a high-throughput drug screening platform. You will help define the unmet needs for cross-functional workflows and will establish/execute processes that will enable insitro’s iPSCs platform to operate successfully with regard to cell management and screening. This role provides the opportunity to collaborate with a highly talented multidisciplinary team as you develop cutting-edge activities in a state-of-the-art environment with the aim to accelerate machine learning based drug discoveries. Additional responsibilities include close partnership with our data and process engineering teams to drive the integration of cytometry-based protocols into semi-automated pipelines.

Your primary duties will be to: 

  • Work with cross-functional teams to define/execute flow based strategies for the QC, banking and target validation of iPSCs derived models for multiple therapeutic areas (i.e. liver and CNS), including sub-population isolations or functional assays; 
  • Lead the efforts for the optimization, transfer and troubleshooting of best-class flow based analytical methodologies for protein, lipids or mRNA (flow-FISH) detection; 
  • Contribute to the identification and development of next-generation technologies (i.e. CITE-Seq) to exercise your creativity and passion for innovation;  
  • Assist with cell sorting and cytometric analysis using a still growing equipment park (CytoFlex, MA900 sorter) ;  
  • Provide expert knowledge and assistance for research experimental design and data management/analysis/interpretation related to cross-functional programs/teams and present findings to project teams;
  • Work closely with automation and bioinformatics experts to implement robust and high throughput sample preparation, high content screening and analysis workflows.
  • Partner with data scientists and machine learning experts to establish flow derived datasets that permit identification of features to predict/support results obtained from disease-specific assays; 

You will be joining a biotech startup that has long-term stability due to significant funding, but yet is very much in formation. A lot can change in this early and exciting phase, 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. or recent PhD in a technical field (immunology, proteomics, pharmacology) or equivalent practical experience
  • Broad experience with cell sorting and state-of-the-art cell analysis technologies applied in primary human cells from multiple lineages (i.e. iPSCS derived); 
  • Proficient with flow analytical tools (i.e., SonyMA900, MacsQuantify, FlowJo or equivalent), for multi-dimensional data acquisition, processing and presentation; 
  • Relevant experience in a scientific role with recognized expertise in the application of flow cytometry techniques to biomedical or preclinical research projects, from experimental design to documentation;
  • Clear communication techniques and teaching skills, with the ability to introduce flow cytometric techniques/analysis to both experienced and novice users;
  • Experience collaborating with data scientists or computational biologists, engineers and/or experimental biologists;
  • Experience working as part of a high-performance team, including goal setting, and contributing to a culture of effective, high-quality methods development and reducing those methods to a practical implementation;
  • Demonstrates independence and adaptability in front of multiple demands and rapid changes;
  • Familiarity with automated instrumentation and associated coding language, while not required, would be a plus for future implementations, 
  • Other criteria will include: a record of publications in a relevant scientific discipline; excellent teamwork, communication, time management and organization skills
  • Passion for making a difference in the world

Benefits at insitro

  • Excellent medical, dental, and vision coverage
  • Open vacation policy
  • Team lunches (catered daily)
  • Commuter benefits
  • Paid parental leave


About insitro

insitro is a data-driven drug discovery and development company using machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients. The company is applying state-of-the-art technologies from bioengineering to create massive data sets that enable the power of modern machine learning methods to be brought to bear on key bottlenecks in pharmaceutical R&D. The resulting predictive models are used to accelerate target selection, to design and develop effective therapeutics, and to inform clinical strategy. insitro was launched in 2018 with a Series A of $100M funded by top investors including a16z, Arch Venture Partners, Foresite Capital, GV, and Third Rock Ventures.

The company has announced collaborations with Gilead Sciences in the area of NASH (2019) and Bristol Myers Squibb in the area of ALS (2020) and, in mid 2020, completed a Series B financing of $143M including current investors and new investors Canada Pension Plan Investment Board (CPP Investments), T. Rowe Price, BlackRock, Casdin Capital and other leading investors. The company is located in South San Francisco, CA. For more information about insitro, please visit the company’s website at www.insitro.com 

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  • Location
    South San Francisco, California
  • Department
    Translational Science
  • Employment Type