QSP Modeller for In Silico Trials (Hybrid)

Discover International; Lyon; Hybrid; EUR 55,000 - 90,000; Full time

Benefits offered by this job

Two remote days per week

Company benefits

Flexible working

Job summary

Discover International is seeking a QSP Modeller to build in silico disease and drug models, calibrate them with data, and run large-scale simulations across virtual populations. You will apply advanced mathematical methods and ML, delivering results through reports and client presentations.

The role requires MSc/PhD in a quantitative field, strong modelling background, and proficiency in Python/R. The position offers hybrid work with up to two remote days per week.

Qualifications

• Experience with mathematical modelling and systems biology.
• Experience with Python or R.
• Professional proficiency in written and spoken English.
• Collaborative, proactive approach with time-sensitive work.

Responsibilities

• Build in silico disease and drug models from literature through development.
• Calibrate models against data and integrate into larger systems.
• Run large-scale simulations on virtual populations.
• Apply ODE, PDE and Monte Carlo methods, ML, statistics and outlier detection.
• Present results through scientific reports and client-facing presentations.
• Contribute to evolution of the simulation platform.
• Participate in project meetings with potential client interaction.

Skills

Mathematical modelling

Systems biology

Python

English proficiency

Education

MSc/PhD in quantitative field

Job description

Discover International is seeking a QSP Modeller to build in silico disease and drug models, calibrate them with data, and run large-scale simulations across virtual populations. You will apply advanced mathematical methods and ML, delivering results through reports and client presentations.

The role requires MSc/PhD in a quantitative field, strong modelling background, and proficiency in Python/R. The position offers hybrid work with up to two remote days per week.