ML Research Scientist - Computational Biologist/Bioinformatics

Posted 5 Days Ago
Be an Early Applicant
7 Locations
In-Office or Remote
235K-270K Annually
Senior level
Artificial Intelligence • Biotech
The Role
Lead the design and deployment of large-scale bioinformatics and omics pipelines spanning genomics, transcriptomics, and proteomics. Integrate multimodal biological data with machine learning, develop reproducible analysis frameworks, benchmark predictive models, and collaborate with wet-lab scientists to guide molecular engineering and experimental campaigns. Contribute novel computational biology algorithms, research roadmaps, and scientific leadership.
Summary Generated by Built In

Merge Labs is a frontier research lab with the mission of bridging biological and artificial intelligence to maximize human ability, agency and experience. We’re pursuing this goal by developing fundamentally new approaches to brain-computer interfaces that interact with the brain at high bandwidth, integrate with advanced AI, and are ultimately safe and accessible for anyone to use.

About the team:

Our Bio team designs, builds, and characterizes the biotechnologies that form the foundation of next-generation brain-computer interfaces. We combine molecular engineering, synthetic biology, neuroscience and advanced physical methods such as ultrasound to establish less invasive, high-bandwidth connections with neurons. The Bio team develops our core molecular technologies, validates their performance in vitro and in vivo, and demonstrates their advanced capabilities in animal models. We build custom experimental setups and pipelines and collaborate closely with engineers and data scientists. We work across disciplines to come up with creative ideas and solve some of the most challenging problems in biotechnology.

About the role:

We’re hiring a Senior / Principal Computational Biologist (Bioinformatics / Omics) to lead the design and deployment of large-scale omics pipelines, integrate multi-modal biological data, and collaborate with ML teams to uncover mechanistic and predictive insights. You’ll architect data processing frameworks that convert raw omics data into clean, analysis-ready datasets and build ML-integrated pipelines that extract deeper meaning from this data. Over time, you’ll help translate these into predictive frameworks that accelerate molecular engineering, inform experimental campaigns, and enable the discovery of highly functional molecules.

In this role, you will:

  • Build the scientific and engineering scaffolding for bioinformatics and computational biology writ-large. Design, optimize, and maintain pipelines for genomics, transcriptomics, and proteomics data.

  • Collaborate with wet-lab scientists to define tractable optimization objectives and encode domain specific priors and constraints.

  • Prototype modeling frameworks using internal and public datasets; benchmark and validate performance.

  • Serve to non-domain experts for democratization of first-principles analysis

  • Stay up-to-date with the latest research in computational biology and prototype novel algorithms that can be deployed to improve the company’s discovery or development workflows.

  • Contribute to the long-term research roadmap and serve as a thought-leader for scientists.

You might thrive in this role if you have:

  • Deep experience with omics data analysis (bulk and single-cell) and bioinformatics pipelines.

  • Expertise in Python and/or R; fluency with workflow management tools (e.g. Nextflow / Dagster)

  • Proficiency in Python / PyTorch / Jax and comfort writing clean, reproducible production grade code.

  • Experience bridging computational biology and experimental science—working with sparse, noisy, and or high-cost data.

  • A collaborative, systems-level mindset.

Nice to have

  • Familiarity with neuroscience

  • Familiarity with transfer-learning paradigms

If you're excited about this role but don't meet every qualification, please apply. As we build, we're hiring for complementary strengths to form a high-impact team.
For more information about hiring at Merge, please visit our Hiring FAQ

Merge Labs does not discriminate on the basis of race, color, religion, national origin, age, sex, sexual orientation, gender, gender identity, gender expression, marital status, physical or mental disability, medical condition, genetic information, family status, ancestry, citizenship, U.S. military (state and federal) and veteran status, or any other legally protected status. It is our intention that all applicants be given equal opportunity and that selection decisions are based on job related factors. We are an equal opportunity employer.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing [email protected].

Skills Required

  • Deep experience with bulk and single-cell omics data analysis
  • Experience designing and maintaining bioinformatics pipelines
  • Expertise with Python and/or R
  • Fluency with workflow management tools such as Nextflow or Dagster
  • Proficiency with Python, PyTorch, and/or JAX
  • Ability to write clean, reproducible, production-grade code
  • Experience bridging computational biology and experimental science
  • Experience working with sparse, noisy, or high-cost data
  • Familiarity with neuroscience
  • Familiarity with transfer-learning paradigms
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The Company
HQ: San Antonio, TX
32 Employees
Year Founded: 2025

What We Do

Merge Labs is a research lab with the long-term mission of bridging biological and artificial intelligence to maximize human ability, agency and experience. Join us: merge.io/careers

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