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Job Title: Senior Computational Biologist

About Us:

Entact Bio is a preclinical stage biotechnology company developing a new class of drugs that enhance the function of beneficial proteins. Launched by a founding team deeply rooted in deubiquitinase (DUB) biochemistry, chemical biology, disease biology, and small-molecule drug development, Entact has designed its proprietary Encompass™ platform to create enhancement-targeting chimeric (ENTAC™) medicines. ENTACs harness the ability of DUBs to regulate proteins. By leveraging this natural cellular mechanism to enhance protein function, Entact is expanding the universe of treatable diseases. 


  • Lead the methodological development and implementation of Entact Bio’s in silico drug discovery platform
  • Inform target/DUB selection and prioritization with testable hypotheses by identifying, curating, and analyzing large-scale omics datasets/databases with existing or new computational approaches
  • Collaboratively support internal mass spectrometry-based proteomics, including the design, prototyping, and implementation of computational pipelines for MS-based assays
  • Actively contribute to research efforts with project-based support and collaboratively proposing and designing experiments with other scientists
  • Maintain frequent and clear communication across internal and external team members, providing timely and interpretable analysis results to the scientific team and management
  • Maintain up-to-date awareness of emerging computational biology methods and applications

Who You Are:

  • Highly versatile and motivated computational biologist:A scientist with strong foundational knowledge and skillset with the willingness to expand into new and dynamic areas of science
  • Openly collaborative and communicative: An outward facing scientist and teammate who thrives in a scientifically diverse, fast-paced, team-oriented, start-up environment and is comfortable interfacing across disciplines
  • Growth mindset: An individual that is continually learning and willing to adapt and succeed in a dynamic environment
  • Highly organized: Strong time management and planning skills


  • PhD or Master's degree in computational biology, bioinformatics or other related discipline with one or more years of experience applying quantitative approaches towards biological applications.
  • Experience developing methods for processing and analyzing high-throughput omics data
  • Experience in development of computational methods for processing and extracting biological data from mass-spectrometry-based proteomics datasets
    • Familiarity with current state of the art methods for mass-spectrometry based proteomics data analyses and methodologies (e.g. TMT and Label free) and their underlying statistical principles
  • Experience in delivering testable hypotheses and insights from complex high-dimensional biological data
  • Strong knowledge of applied statistics and machine learning, experience with generative models a plus
  • Strong scientific programming skills in Python or R, and experience with cloud computing platforms (AWS, Google Cloud, Azure)
  • Demonstrated ability to lead cross-functional projects, collaborate with other scientists and effectively communicate scientific challenges, solutions and results
  • Demonstrated ability to work as a team player in a dynamic, fast-paced environment focused on deliverables
  • Exceptional communication skills as demonstrated by notable publications and presentations
  • Continuously seeking education with an ability to quickly adapt to new information

As a member of our diverse and growing team, you’ll help shape us into a company that takes its scientific mission seriously while providing a positive and supportive workplace environment and culture. With your insights, passion and talent – we’ll bring novel therapeutics to the patients who need them the most.

We are an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.