Computational Biologist, Statistical Genetics

Berlin / NYC – Hybrid / On-site

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Join Pheiron – Flipping the Odds in Drug Development

90% of attempts to develop drugs fail, and bringing a new therapeutic to market costs between $1-2bn. Thousands of diseases are without cures. At Pheiron, our mission is to change that. Using AI and large-scale human multi-omic data (trillions of datapoints across millions of individuals), we generate novel insights into human biology that revolutionize how drugs are discovered and developed. Our work at the intersection of AI, medicine, and biotech empowers drug developers to make groundbreaking discoveries and develop the next generation of therapeutics!

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About the role

We are looking for a high agency Computational Biologist who loves population cohorts and will help us mature our PheironGPS platform in an iterative and fast-moving environment. In that role, you will be integrating the rich genetic, multiomic, and clinical data from millions of individuals across the largest and most deeply phenotyped population cohorts on the globe to generate evidence on who gets disease in the first place, what drug should be prioritized, and in whom they work best. Our partners include some of the most innovative biotech and pharmaceutical companies in the world. You will collaborate closely with the product team to learn which evidence is most important for our partners. You will be a key part of the effort to implement this evidence across the industry to increase the probability that the medicine of the future reaches patients in need. 

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In this role, you will:

• Own key parts of our computational platform, including specific population cohorts and parts of the evidence generation
• Optimize our pipelines for iteration speed, quality of the evidence, and scale
• Enable and work closely with the product team to get relevant feedback and iterate on the core evidence generation
• Collaborate with a cross-functional team of scientists, clinicians, and engineers to create cutting-edge evidence, translate it to our partners and communicate it to the wider scientific community

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Your background looks something like:

• 5+ years of relevant experience running large‑scale genetic analyses in population cohorts (e.g., UK Biobank, FinnGen, All of US); skilled in Python/R and workflow orchestration; strong track record of peer‑reviewed publications or product deliverables. Industry or Consortia experience preferred.
• PhD (or equivalent) in Statistical Genetics, Human Genetics, Bioinformatics, Computational Biology, or related field.
• Proficiency with population genetics methods including GWAS/ExWAS, PheWAS, RVATs, PRS, proficiency with cloud computing and version control.
• Proficiency deploying workflows in cloud-based trusted research environments (we use Python, bash, Docker, and Nextflow)
• Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines

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Why Pheiron?

Pheiron is an AI-first research company dedicated to translating data from the world's largest biobanks to benefit patients in need. We push the boundaries of extracting the most critical evidence, integrate it across biobanks, and translate it into evidence that helps the industry discover and develop the medicines of the future.

• You will work directly with data from millions of individuals all across the globe. Your work will directly influence the discovery and clinical development of tomorrow's medicines.
• Lead high‑visibility projects with autonomy and support, present work at national and international scientific conferences.
• Competitive salary + equity, and flexibility to work hybrid/on‑site in Berlin or NYC. We offer visa sponsorship and relocation support.
• Join a team that values curiosity, integrity, and scientific excellence.

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Ready to apply?

Send your CV and a brief note about your coolest project (paper / GitHub repository / else) to join@pheiron.com. We can’t wait to meet you!

‍Pheiron is an equal‑opportunity employer committed to creating an inclusive environment for all.