Description

The candidate will be a core member of a computational team developing and applying cutting-edge AI-driven protein engineering methods to design next-generation biotherapeutics, and will work closely with a dynamic and multidisciplinary team conducting associated protein engineering and preclinical analysis experiments. In particular, the role focuses on analysis and modeling of data collected as part of our diverse biotherapeutic development campaigns, with an initial primary focus on data from immunoassays including immunopeptidomics and T cell activation. The candidate will have the opportunity to build and use bioinformatics tools and pipelines to extract information from these rich datasets and thereby help guide design and engineering of life-altering innovative biotherapeutic agents.

Requirements

Responsibilities

• Key responsibilities center on deploying, applying, evaluating, and improving bioinformatics tools and pipelines to manage, analyze, and interpret data regarding our biotherapeutic development campaigns, initially focusing on immunoassays including immunopeptides and T cell activation, which we use to assess the immune recognition of biotherapeutics.
• Additional responsibilities will include curation and targeted analysis of background Omics data relevant to our biotherapeutics. 
   
  Qualifications
• An MS, or a BS with 1+ years of experience, in Bioinformatics, Quantitative Biomedical Sciences, Computer Science, Statistics, Mathematics, or a related quantitative discipline  
• Practical experience with bioinformatics tools and pipelines for analysis of large-scale biological data in general is required. Experience with immunology data is beneficial. Data analysis and management within cloud-based platforms is beneficial.  
• Proficiency in Python and relevant scientific, bioinformatics, and visualization packages is required. Additional beneficial proficiencies include creation of end-user available tools and web portals, along with use of REST APIs to access public datasets.
• Practical experience in machine learning or image processing and analysis is beneficial