stage 6 mois mathématiques appliquées et modélisation
Based in France
Core
Develop advanced kinetic models and compare frequentist and Bayesian statistical performance for predicting the stability of biological products.
Role type
Applied mathematician (statistical modeling)
Builds
Predictive models for biological product stability
Domain
Biopharmaceutical R&D
Deliverable
production ML models
Required skills
Frequentist statistics, Bayesian statistics, R, Python
Preferred skills
None stated
Technologies
R, Python
Responsibilities
Participate in expert groups for predicting biological product stability; Contribute to improving modeling software and programs; Collaborate with international and multidisciplinary teams; Develop predictive models and R/Python programs; Support deployment of advanced kinetic modeling best practices; Promote new modeling tools; Propose useful statistical methods.
Seniority
Intern
