Principal Scientist, Computational Biology

Principal Scientist, Computational Biology

Millbrae, CA

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 that enable real‑time, molecular‑resolution measurements of protein movement in living cells, thereby unlocking otherwise intractable classes of proteins as drug targets.

We seek a Principal Scientist in Computational Biology to drive diverse early drug discovery efforts across Eikon’s target portfolio. In this key role, the successful applicant will use rigorous analytical skills in close collaboration with diverse discovery scientists to conceive and evaluate complex, progress‑enabling experiments across our target portfolio. A natural collaborator, this individual will draw on substantial experience performing analysis of traditional genomic, chemical biology, and high throughput experiments to elevate the work of others while identifying new targets and defining new drug discovery applications that are enabled by Eikon’s unique technical capabilities.

For this role we seek an experienced, rigorous, and results‑driven computational scientist with a strong track record of making high‑impact contributions in early research drug discovery programs. This person will be an enthusiastic and generous collaborator who is comfortable working in a fast‑paced, cross‑functional environment uniting diverse disciplines and subject‑matter experts skilled in traditional and emergent drug discovery technologies. They will be a curious, detail‑oriented, and strategic thinker who can draw on deep technical and biological knowledge to synthesize data from diverse internal and external sources to resolve nuanced scientific questions.

They are comfortable driving the design, analysis, and evaluation of high throughput and genomics experiments to discover novel biological insights and effectively communicate their outcomes to both technical and non‑technical audiences. This combination of expansive knowledge, good judgment, and passion for drug discovery makes you an inspiration to others and enables you to lead through example and mentorship.

• Use computational approaches to drive drug discovery programs forward in close collaboration with experimentalists across Eikon’s target portfolio.
• Apply statistical, biological, and experimental expertise to evaluate complex experiments and distill information from diverse sources to reach relevant and testable biological conclusions.
• Identify innovative analytical approaches to answering key biological questions, perform analyses to define their appropriate use, and apply these approaches to further therapeutic programs.
• Collaborate with informaticists and engineers to prototype new analytical approaches and broadly enable computational capabilities.
• Mentor junior scientists across functions by providing an example of principled, data‑driven problem solving that is supported by deep engagement with underlying biological questions.
• Contribute to the preparation of scientific publications, presentations, and grant proposals, showcasing the impact of bioinformatics analyses on advancing scientific knowledge.

• PhD or equivalent in a computationally‑aligned field plus 10 years’ relevant industry experience; minimum 5 years’ experience in drug discovery.
• Excellent interpersonal, written, and verbal communication skills, with significant experience collaborating closely with experimental teams and providing mentorship to junior scientists.
• Strong practical expertise in the design, evaluation, and integration of high throughput experiments, as well as deep understanding of relevant statistical techniques.
• Expertise using one or more high‑level programming language (e.g., R, Python) to solve biological problems; well‑versed in modern coding and computing best practices such as cloud deployment, version control,…