Senior Scientist: Biological Modeling and Single Cell Data Sciences
With the advent of genomic sequencing, we can finally decode and process our genetic makeup. We now have more data than ever before but providers don't have the infrastructure or expertise to make sense of said data. Here at Tempus, we believe the greatest promise for the detection and treatment of cancer lies in the deep understanding of molecular activity for disease initiation, progression, and efficacious treatment based on the discovery of unique biomarkers.
We're on a mission to connect an entire ecosystem to redefine how genomic data is used in clinical settings. We're looking to build a laboratory operations team who are passionate and focused on developing state of the art techniques to processing and creating and interpreting vast amounts of genomic and molecular data from patients and from biological models. While developing and screening organoid models directly from patient tumor samples, scientists will collaborate with product, research, and business development teams to develop the most advanced sequencing platform in cancer care.
What you will do:
- Design and execute single cell RNA-seq experiments to generate high dimensional data sets.
- Work with a cutting-edge immunology and biological modeling teams to provide high-quality cellular population analyses, and identify novel populations for further experimental characterization.
- Oversee phenotypic assay development, data quality metrics, structuring of in vitro data, and use computational tools to analyze these data in the context of orthogonal data sets.
- Work in interdisciplinary groups of scientists, engineers and product developers to translate research from single cell data and biological modeling into actionable insights.
- PhD with 6+ years of experience in stem cell, molecular biology, or biochemistry
- Demonstrated experience working with high dimensional data sets such as high throughput screening, CyTOF, multicolor flow cytometry, or single cell RNA-seq
- Fundamental understanding of cancer pathophysiology
- Demonstrated experience with single cell RNA-seq capture and knowledge of library preparations for next-generation sequencing
- Basic fluency in R and Python to generate and run custom scripts for analysis