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🚀 Internship

2024 Intern - Machine Learning And Statistical Modeling In Drug Development

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29d ago

🚀 Summer Internship

San Francisco

AI generated summary

  • The candidate must have a M.Sc. in a relevant field, preferably be involved in a PhD program, or have obtained a PhD within the past 2 years. They should have expertise in statistical modeling and machine learning analysis, particularly in time-to-event modeling or survival analysis. Proficiency in scientific computing programming using Python, Julia, Matlab, R, or Mathematica is required. Excellent communication and collaboration skills, as well as enthusiasm for learning and contributing in a multidisciplinary environment, are also important qualities.
  • The candidate will engage in machine learning and statistical modeling for drug development, contributing to various modeling tasks, presenting results at conferences and meetings, and actively participating in a team-oriented environment.

Summer Internship

Data•San Francisco


  • In addition to building a time-dependent predictive relationship of survival into a QSP model of cancer immunotherapy for (neo)adjuvant trials, the candidate will be responsible for compiling and processing all data necessary for the project, set up the computational framework required for the project, work closely with other modeling and ML/AI scientists and benefit from each other expertise, learn the biology and the clinical aspects of anti-cancer treatments as needed and collaborate with non-modeling scientists from other departments.

Program Highlights

  • Intensive 4-to-6 months, full time (40 hours per week) paid internship.
  • Program start dates are in May/June (Summer).
  • A stipend, based on location, will be provided to help alleviate costs associated with the internship. 
  • Ownership of challenging and impactful business-critical projects.
  • Work with some of the most talented people in the biotechnology industry.


  • M.Sc. in (bio)statistics, physics, mathematics, machine learning or in a relevant computational or engineering field.
  • Candidates currently involved in a PhD program are preferred.
  • Candidates that have already obtained a PhD less than 2 years ago, and willing to gain experience in the pharmaceutical industry, are also encouraged to apply.
  • Required Qualifications:
  • Expertise with statistical modeling, including machine learning analysis, is required.
  • Experience with time-to-event modeling or survival analysis is strongly preferred.
  • Expertise with scientific computing programming using Python, Julia, Matlab, R or Mathematica is required (in order of preference).
  • Preferred Qualifications:
  • Excellent communication, collaboration, and interpersonal skills.
  • Enthusiasm to learn and contribute in a multidisciplinary environment, driven by challenges, scientific curiosity are qualities we are looking for.

Education requirements


Area of Responsibilities



  • Learn and contribute to other modeling tasks, as needed.
  • Summarize results in posters for presentation in internal or external conferences.
  • Contribute to manuscript writing summarizing the accomplished work.
  • Present results at cross-functional teams, department meetings, and/or review committees.
  • Adapt and thrive in an interactive, team-oriented culture.


Work type

Full time

Work mode



San Francisco