Senior/Scientist, Biological Modeling

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

These insights are also experimentally evaluated in our state of the art Biological Modeling Laboratory to accelerate the development of new therapeutic options for patients. We are seeking a Scientist to augment our novel AI powered organoid therapeutic profiling platforms. 

What You’ll Do: 

• Work closely with our strategic pharma partners in discovery and translational research to analyze high content imaging and AI assays including deep learning algorithm readouts of therapeutics in development
• Collaborating with cutting-edge computational biologists, data scientists, and machine learning scientists on experiments and acquisition of high content translational data sets
• Work in a collaborative, interdisciplinary team of scientists and technicians on in vitro systems for cancer biology and immunology including spatial transcriptomics and single cell RNA-seq

 Qualifications:

• PhD with 5+ years of laboratory experience or Master’s degree with 10+ years of laboratory experience
• Demonstrated expertise in cancer biology and translational research
• Experience with projects involving multidisciplinary teams or collaborations
• Fundamental understanding of cancer pathophysiology and/or immunology

Preferred Candidates will Possess:

• Experience in large scale data set analysis from high dimensional data sets such as high throughput screens and arrayed or pooled functional genomic screens
• Proficiency in R and/or Python 
• Rigorous attention to detail and ability to coordinate complex experimental procedures and workflows within a multidisciplinary team