Scientist / Senior Scientist, Human Genetics

Application ends: April 30, 2024
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Job Description

An exciting opportunity is available for an exceptional, highly motivated Statistical Geneticist to join the Institute of Medicine (IoM) at Altos Labs. The Scientist / Sr. Scientist will report to the Director of Human Genetics and play a pivotal role in developing and conducting research at the interface of discovery and translation.The candidate will work in a highly dynamic and cross-functional environment, collaborating with the Institutes of Science and the Institute of Medicine, and spanning multiple therapeutic areas. The successful candidate will have strong scientific training and a demonstrated track record of leading and conducting Human Genetics research in academia, biotechnology or the pharmaceutical industry.


  • Harvest and analyze genetic and genomic variation to dissect the molecular and cellular basis of disease. Use those insights to enable and facilitate the development of transformative medicines
  • Create and foster strong partnerships with groups at the Altos Institutes of Science
  • Plan and conduct genetics research related to areas such as chronic disease risk and modifiers thereof, cellular resilience, stress response, and energy metabolism
  • Collaborate with information technology, computational biology, and machine learning specialists to enable and streamline genetic data analysis.
  • Contribute to a team culture that promotes continuous improvement, ownership, professional growth, and inclusion

Minimum Qualifications

  • PhD in Statistical Genetics or a related discipline, with experience in an academic or industry research setting
  • Track record of publications in peer-reviewed journals, and/or impactful contributions in the biotech / pharmaceutical industry
  • Excellent collaboration skills and eagerness to thrive in the highly collaborative environment across Altos
  • Strong knowledge of quantitative human genetics (GWAS, QTL mapping, etc.) and statistical modeling
  • Expertise in genetic association analyses, summary statistics-based meta-analysis, fine-mapping, colocalization, Mendelian Randomization
  • Experience with large-scale biobank data (e.g. UK Biobank)
  • Proficiency in relevant programming languages (R, Python, etc.)
  • Team player and effective communicator, able to bridge the gaps between computational disciplines and wet-lab science

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Preferred Research Skills

Knowledge of cloud computing and machine learning principles

Experience with analyses using functional genomics data, especially in conjunction with genetic associations (e.g., scRNA-Seq, ATAC-Seq, etc.)

How should applicants apply?
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