Data Science & Machine Learning Intern: Statistical Genetics

Key Skills

AWS, Dask - Python library, EBI GWAS Catalog, ExAC, Git, gnomAD, Google Cloud Platform (GCP), Java Programming, Large scale data processing, Mercurial, NoSQL, NumPy, OpenCV, Pandas, PheWAS, Python Programming, Scikit-learn, SciPy, SQL, UK Biobank

Job Description

Global drug development productivity is declining exponentially, with an overall failure to develop effective treatments for many increasingly prevalent complex diseases affecting millions of patients per year. We seek to solve this by combining cutting-edge machine learning techniques with recent advances in life sciences to drastically improve how drugs are discovered and developed.

This summer we are looking for highly motivated interns looking to work at the intersection of machine learning and life sciences. As a statistical genetics intern, you will conduct genetic association studies and other statistical genetics techniques that involve integration of genetic, genomic and clinical data to guide in vitro disease model development. You will also work closely with a cross-functional team of machine learning scientists, software engineers, life scientists, bioengineers, and medical scientists to integrate human level data with our high-throughput in-house in vitro genomic and phenotypic data to identify therapeutic targets and develop drugs that have high efficacy and low toxicity.

Insitro has a highly dynamic and collaborative culture in a custom-built open office in South San Francisco. You will work closely with machine learning engineers and scientists, biologists, chemists, microscopy experts, and automation engineers. You will be mentored by one of our senior researchers, who has significant experience in machine learning for genetics or statistical genetics in metabolism, neuroscience, or oncology. You will also attend our machine learning team meetings and will be exposed to a diverse set of novel technologies and machine learning concepts that tackle various biological questions.

Join us, and help make a difference to patients!

About You

• Working towards a BS, MS, or Ph.D. in an engineering, computer science, mathematics, statistics, life science, chemistry, physics, or a related discipline
• Proficiency in one or more general-purpose programming languages. We primarily use Python
• Demonstrated ability to use and develop cutting edge statistical and machine learning methods inspired by real problems
• Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs)
• Experience with germline single nucleotide variants, structural variants, and/or somatic variants
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Passion for making a difference in the world

Nice to Have

• Hands-on experience with genetic association testing (eQTL mapping, GWAS, EWAS, PheWAS, etc.) or experience mining modern, large-scale genetic databases (e.g. ExAC/gnomAD, UK Biobank, EBI GWAS Catalog, etc.)
• Experience in Linux environment, database languages (e.g., SQL, No-SQL) and version control practices and tools such as Git or Mercurial
• Familiarity with the SciPy/PyData ecosystem (numpy, pandas, scipy, dask etc.)
• Familiarity with cloud computing services (AWS or GCP)

Intern Benefits

• Excellent medical, dental, and vision coverage; insitro pays 100% of premiums for employees
• Excellent mental health and well-being support
• Access to free onsite baristas and cafe with daily lunch and breakfast
• Access to free onsite fitness center
• Commuter benefits
• Competitive pay
• Flexible work schedule (on site and remote)