Tracking Eikon Therapeutics: Hiring Trends After $350M in Funding

Eikon Therapeutics recently caught our eye after reportedly raising a $350.7 million series D round. The company is developing novel small molecule therapeutics by tracking protein behavior in living cells, with a pipeline focused in oncology and immunology1.

Eikon was founded by pioneers2 in super-resolution microscopy, specifically in single molecule tracking (SMT) techniques3. Their approach involves using proprietary SMT microscopes and software to screen protein-ligand interactions in live cells, generating huge datasets4 in the process.

Current Hiring Focus

PharmaPayWatch.com classification of Eikon Therapeutics job postings as of March 3, 2025. Eikon job postings indicate a focus on Clinical Operations, Quality and Regulatory, Medical Affairs, and Research.
PharmaPayWatch.com classification of Eikon Therapeutics job postings as of March 3, 2025. Eikon job postings indicate a focus on Clinical Operations, Quality and Regulatory, Medical Affairs, and Research.

Eikon describes itself as “clinical stage” and that positioning is reflected in the job posting data. As of March, their hiring patterns are spread between Clinical Operations, Medical Affairs, Quality & Regulation, and Research, without any recent commercial focused jobs.

Here’s a few notable positions:

Job Data and Ongoing Coverage

You can follow our Eikon Therapeutics page to stay up to date with Eikon hiring patterns and trends. PharmaPayWatch tracks job posts from many biotech and pharma companies, and we maintain a job board with only jobs posted in the last 14 days. Follow us on Bluesky @PharmaPayWatch.com.


  1. The later stage pipeline is focused on oncology. ↩︎

  2. Eikon was co-founded by Eric Betzig, who won the 2014 Nobel Prize in Chemistry (along with Stefan Hell and William Moerner). Along with Betzig, Robert Tjian, Luke Lavis, Xavier Darzacq are listed as co-founders. ↩︎

  3. Super-resolution microscopy are techniques that allow you to achieve resolutions better than the diffraction limit of light. There are two primary types, one is “direct”, in that you selectively deactivate fluorophores to minimize non-specific illumination (e.g., STED), and the others are known as “stochastic” methods that take advantage of selective activation of fluorophores and collection of a large number of images, allowing you to calculate the location of a fluorophore down to a few nanometers (e.g., PALM/STORM and other single molecule localization techniques). Read more on these techniques on wikipedia↩︎

  4. Eikon claims to generate nearly a petabyte of data per day (!) https://www.eikontx.com/platform/ (see AI & Machine Learning tab, unfortunately this is not a very friendly website to cite or work with). ↩︎

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