Data Science & Machine Learning Intern: Advanced ML Technologies

Key Skills

AWS, Bayesian networks, Causal inference, Dask - Python library, Gaussian Process, Generalization, Generative AI, Google Cloud Platform (GCP), JAX framework, Linux Operating system, Machine learning techniques, NoSQL, NumPy, Pandas, Probabilistic Graphical Models, Python Programming, PyTorch, SciPy, SQL, Statistical modeling

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 (and off-season on a running basis subject to availability) we are looking for highly motivated interns looking to work at the intersection of machine learning and life sciences. As an Advanced ML intern, you will work on cutting edge algorithms across generative & probabilistic modeling/programming, Bayesian Inference, Gaussian Processes, Bayesian Neural Networks, causal inference, representation learning, and robustness, to lay the foundations for the next generation of systems that will impact drug discovery, across imaging, biology (genetics & genomics), chemistry, and clinical data analysis.

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 foundational machine learning and will pair up with teams working on specific application areas to ground the practicality of the work. 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 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.
• Extensive experience using Pytorch and/or Jax
• 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)
• Research experience on topics related to Robust Representation Learning, Efficient Generalization, Generative Modeling, Probabilistic Modeling, Causal Inference, probabilistic programming, Bayesian Modeling/Bayesian NNs, Gaussian Processes, and more topics.
• 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

• Experience using and building probabilistic programming languages
• 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)

Compensation & Benefits at insitro

Our target starting salary for successful US-based applicants for this role is $50 - $55 per hour. To determine starting pay, we consider multiple job-related factors including a candidate’s skills, education and experience, the level at which they are actually hired, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.

In addition, insitro also provides our interns:

• 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)