Computational Biologist

Biohub•Chicago, IL

1d•Hybrid

About The Position

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team The Biohub is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. The Biohub focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies. Our Vision We pursue large scientific challenges that cannot be pursued in conventional environments We enable individual investigators to pursue their riskiest and most innovative ideas The technologies developed at the Biohub facilitate research by scientists and clinicians at our home institutions and beyond Diversity of thought, ideas, and perspectives are at the heart of Biohub and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution. The Opportunity The Biohub Chicago is seeking an exceptional Computational Biologist, Spatiotemporal Multi-Omics to join our growing team. We are looking for a creative and collaborative bioinformatics researcher who is excited to build the analytical foundation for our spatiotemporal multi-omics technology platform.

Requirements

PhD in bioinformatics, computer science, statistics, computational biology, biomedical engineering or a related quantitative discipline.
Minimum 2 years of experience in developing bioinformatic methods, analysis pipelines, or software tools for biological data using appropriate programming language.
Minimum of 1 year of experience in at least one of the following areas: spatial data analysis, multi-omics integration, or machine learning for biological applications.
A strong record of research productivity, including publications, open-source contributions, or both.
A collaborative mindset, strong communication skills, and enthusiasm for working closely with wet-lab teams.

Nice To Haves

1+ year of experience with imaging mass spec (e.g., MALDI)
1+ year of experience with single-cell proteomics and/or metabolomics
1+ year of experience building visualization tools, or scientific software.

Responsibilities

Develop data analysis workflows for spatiotemporal and multi-omics datasets.
Build visualization tools that enable exploration and interpretation of complex biological data across space and time.
Integrate proteomics, metabolomics, and related datasets, and explore machine learning or transfer learning approaches to support biological discovery.
Collaborate closely with experimental scientists, communicate findings clearly, and contribute to publications, presentations, and open-source software as appropriate.