Computational Biologist - Dynamic Systems Modeling H/F)

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Computational Biologist - Dynamic Systems Modeling H/F), Gif-sur-Yvette

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Client:

Servier

Location:

Gif-sur-Yvette, France

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

7952eb8853b3

Job Views:

3

Posted:

24.04.2025

Expiry Date:

08.06.2025

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Job Description:

Role Description

We are seeking a System Biologist to join our Data Sciences & Data Management team, focusing on the dynamic modeling of biological systems. The ideal candidate will apply their expertise in mathematical modeling and computational biology to drive insights into biological processes. This role will work at the intersection of biology, mathematics, and data science, contributing to innovative drug discovery and development pipelines.

The associated activities will be carried out in collaboration with a multidisciplinary team including therapeutic project managers, biologists, chemists, computational chemists, bioinformaticians, and data engineers.

Background

PhD in Computational Biology, Computational Physics, Bioinformatics, Computational Biophysics, or Computational Mathematics applied to Biology, or a related field.

Required Qualifications

Mathematical & Modeling Expertise:

• Solid foundation in ODE modeling, parameter inference, and statistical validation.
• Experience with stochastic and mechanistic modeling frameworks.
• Strong skills in Python (including PySB, NumPy, SciPy, PyTorch/TensorFlow, Pandas, Matplotlib).
• Knowledge of differential equations systems applied to biology, chemistry, or pharmacokinetics/pharmacodynamics.
• Understanding of molecular biology, biochemistry, or pharmacology.
• Familiarity with high-throughput experimental data (e.g., transcriptomics, proteomics).
• Knowledge of biological databases (e.g., Chembl, Encode, GEO).
• Data analysis and machine learning techniques using Python and Scikit-Learn (clustering, dimensionality reduction, data preprocessing, statistics).
• Experience with Physics-Informed Neural Networks (PINNs) and integration with experimental datasets is a strong plus.

Preferred Skills

• Experience with machine learning and AI techniques applied to biological data.
• Knowledge of knowledge graphs & graph theory.
• Knowledge of pharmacokinetics/pharmacodynamics (PK/PD) modeling.
• Experience with cloud computing platforms and tools for scalable data analysis.
• Experience with bioinformatics tools and databases.
• Ability to work collaboratively in multidisciplinary teams and communicate complex scientific concepts effectively.
• Strong teamwork skills are mandatory.
• Pragmatic and result-oriented approach.
• Ability to manage multiple projects respecting deadlines.
• Innovative and curious mindset.