Machine Learning Intern - QSP Surrogate Modeling & PyTorch

Nova In Silico company; Lyon; Hybrid; EUR 8,900 - 13,000; Part time

Job summary

Nova In Silico is a health tech company in Lyon that develops an in silico clinical trial platform jinkō to simulate drug efficacy and optimize development. The internship provides significant responsibilities and a steep learning curve within a highly motivated team.

You will work on stochastic gradient estimation for QSP surrogate models, review literature, prototype algorithms, and help integrate solutions into Nova's simulation platform.

Qualifications

• Proficiency in machine learning using Python and PyTorch.
• Experience with NLME models and statistical modelling is a plus.
• Professional English communication is required.

Responsibilities

• Review the literature on relevant ML algorithms.
• Prototype the stochastic gradient algorithm under Nova's constraints.
• Evaluate benchmark cases against the SAEM alternative.
• Integrate the solutions into Nova's simulation platform.

Skills

Python

PyTorch

NLME modelling

Statistical modelling

Tools

NLME

ML in Python

Job description

Nova In Silico is a health tech company in Lyon that develops an in silico clinical trial platform jinkō to simulate drug efficacy and optimize development. The internship provides significant responsibilities and a steep learning curve within a highly motivated team.

You will work on stochastic gradient estimation for QSP surrogate models, review literature, prototype algorithms, and help integrate solutions into Nova's simulation platform.