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Eikon Therapeutics

Scientist, Computational Biology

Millbrae, California, United States

Location
Millbrae, California, United States
Work
Not stated
Employment
Not stated
Level
Not stated
Function
Science & research
Pay
$142K – $171.2K a year (read from the ad)
Posted
5 weeks ago

Pay and the market here

The top of this role’s range, $171K a year, is 10% below the median of $190K for science jobs in California (middle half $126K – $300K, 708 jobs that state pay).

5 science jobs open in Millbrae: 0% remote, 3 posted in the last 30 days.

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About the role

Eikon Therapeutics is a new biopharmaceutical company employing revolutionary technology at the intersection of chemistry, engineering, computation, and biology to discover novel treatments for life-threatening diseases. Eikon’s discovery platform is built on groundbreaking innovations from its founders (Nobel Prize, 2014), culminating in the creation of microscopes which enable real time, molecular-resolution measurements of protein movement in living cells, thereby unlocking otherwise intractable classes of proteins as drug targets.

Position

We are seeking a Scientist in Computational Biology to drive diverse early drug discovery efforts across Eikon's target portfolio. In this key role, the successful applicant will serve as the subject matter expert for analyzing high-dimensional data, including bulk and single-cell transcriptomic datasets, and will use rigorous analytical skills in close collaboration with diverse discovery scientists to conceive, design, and evaluate complex, progress-enabling experiments across our target portfolio. This person will perform reproducible analyses across transcriptomic, genomic, and other high-dimensional datasets, adapting methods as appropriate to fit each scientific question, and will build and extend internal computational tools and workflows while overseeing external analysis efforts as needed.

About You

You are an experienced, rigorous, and results-driven computational scientist with the ability to deliver high-impact contributions that advance early drug discovery programs. You are a generous and enthusiastic collaborator, skilled in both established and emerging drug discovery technologies, and comfortable operating in a fast-paced, cross-functional environment that brings together diverse disciplines and subject matter experts.

You are a curious, detail-oriented, strategic thinker who draws deep technical and biological knowledge to synthesize data from diverse internal and external sources to resolve nuanced scientific questions. You will bring hands-on expertise in analyzing high-dimensional datasets - including bulk and single-cell/single-nucleus transcriptomic data - and are adept at building, adapting, and maintaining computational pipelines and workflows.

What You’ll Do

  • Acts as the go-to expert for analyzing high-dimensional datasets, such as bulk and single-cell/single-nucleus transcriptomic data.
  • Partners closely with scientists throughout Discovery to design, execute, and interpret in vitro and in vivo studies that advance projects across the portfolio.
  • Conducts rigorous and reproducible analyses spanning transcriptomic, genomic, and other complex datasets, tailoring analytical methods to the scientific question at hand.
  • Builds and enhances internal computational tools and pipelines, while overseeing external analytical partnerships when needed.
  • Follows sound practices in code and data management - including version control and workflow orchestration - and proactively suggests process improvements.
  • Contributes to the preparation of scientific publications and presentations showcasing the impact of complex data analysis on advancing scientific knowledge.

Qualifications

  • PhD in bioinformatics, computational biology, or a related quantitative field.
  • Proven experience analyzing complex biological datasets across one or more technical modalities, such as bulk, single-cell, or spatial transcriptomics, ChIPseq, ATACseq, CRISPR screens, high throughput proteomics, etc.
  • Demonstrated hands-on experience in oncology target discovery and validation, from hypothesis generation through target prioritization
  • Minimum of one first-author publication in a peer-reviewed, reputable journal.
  • Experience working with public datasets such as DepMap, UK Biobank, TCGA, GTEx, ENCODE, and Human Cell Atlas.
  • Expertise using one or more high level programming language (e.g., R, Python, or similar) to solve biological problems; well versed in modern coding and computing best practices such as cloud deployment, version control, containerization, etc.
  • Excellent interpersonal, written, and verbal communication skills.
  • Internship or industry exposure highly desirable.

At Eikon, employee compensation also includes bonus and equity compensation, in addition to several generous benefit programs, including:

  • 401k plan with company matching
  • Medical (premiums covered by Eikon at 95%), dental and vision insurance (premiums covered by Eikon at 100%)
  • Mental health and wellness benefits
  • Weeklong summer and winter holiday shutdowns
  • Generous paid time off and holiday policies
  • Life/AD&D Insurance (premiums covered by Eikon at 100%) and optional supplemental employee-paid life/AD&D policies
  • Enhanced parental leave benefit
  • Daily subsidized lunch program when on-site

The expected salary range for this role is $142,000 to $171,150 depending on skills, competency, and the market demand for your expertise.

Eikon is proud to be an equal opportunity employer and will consider all qualified applicants for employment.

We are currently not accepting any new third-party agencies or firms at this time. Please do not forward unsolicited agency resumes to our website, employees or Human Resources. Eikon Therapeutics will not pay fees to any third-party agency or firm associated with unsolicited resumes.

Source

Posted by Eikon Therapeutics on their own hiring page, job-boards.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 11:25 UTC; the original is the reference.

View the original ad ↗

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