ML Research Scientist - Computational Biologist/Bioinformatics
About The Position
Merge Labs is a frontier research lab focused on bridging biological and artificial intelligence to enhance human ability, agency, and experience. We are developing advanced brain-computer interfaces that offer high-bandwidth interaction with the brain, integrate with sophisticated AI, and are designed for safety and accessibility. The Bio team is responsible for designing, building, and characterizing the biotechnologies that underpin these next-generation BCIs. This involves a multidisciplinary approach combining molecular engineering, synthetic biology, neuroscience, and advanced physical methods like ultrasound to create less invasive, high-bandwidth neural connections. The team develops core molecular technologies, validates their performance in vitro and in vivo, and demonstrates their capabilities in animal models, while also building custom experimental setups and pipelines and collaborating with engineers and data scientists. We encourage creative problem-solving across disciplines to tackle complex biotechnology challenges. We are seeking a Senior / Principal Computational Biologist (Bioinformatics / Omics) to spearhead the design and implementation of large-scale omics pipelines. This role involves integrating multi-modal biological data and collaborating with ML teams to derive mechanistic and predictive insights. The successful candidate will architect data processing frameworks to transform raw omics data into analysis-ready datasets and develop ML-integrated pipelines for deeper data interpretation. The ultimate goal is to translate these efforts into predictive frameworks that accelerate molecular engineering, guide experimental strategies, and facilitate the discovery of highly functional molecules.
Requirements
- 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 Haves
- Familiarity with neuroscience
- Familiarity with transfer-learning paradigms
Responsibilities
- Build the scientific and engineering scaffolding for bioinformatics and computational biology.
- Design, optimize, and maintain pipelines for genomics, transcriptomics, and proteomics data.
- Collaborate with wet-lab scientists to define optimization objectives and incorporate domain-specific priors and constraints.
- Prototype modeling frameworks using internal and public datasets; benchmark and validate performance.
- Serve as a resource for non-domain experts to facilitate the democratization of first-principles analysis.
- Stay current with the latest research in computational biology and prototype novel algorithms to enhance the company’s discovery or development workflows.
- Contribute to the long-term research roadmap and act as a thought leader for scientists.
Benefits
- We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing [email protected].
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
