Publisher
source

INRAE

PhD in Hybrid Modeling, Digital Twins, and Machine Learning for Microbial Fermentation Systems INRAE in France

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhD opportunity for 3 years.

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Country

France

University

INRAE

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Keywords

Computer Science
Biomedical Engineering
Chemical Engineering
Biology
Mathematics
Mathematical Modeling
Computational Biology
Digital Twin Technology
Dynamical Systems
ML

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About this position

PhD opportunity in Hybrid Modeling & Digital Twins within the Engineering Digital Twins (EDT) research program.

The project, titled Compositional Hybrid Digital Twins Models, focuses on combining mechanistic models and machine learning to build flexible and reusable digital twin architectures. The case study is microbial fermentation ecosystems, with an emphasis on understanding, simulating, and predicting the dynamics of complex biological systems.

Research themes include hybrid modeling, model composition, scientific machine learning, dynamical systems, multi-fidelity modeling, and applications to microbial communities and fermentation processes.

Supervision is listed as Lorenzo Sala (INRAE, MaIAGE) and Julien Deantoni (Université Côte d'Azur). The position is described as fully funded and lasts 3 years.

Ideal candidates should have a background in applied mathematics, computer science, computational biology, or a related field, and be interested in interdisciplinary research.

For full details and application instructions, use the provided application link and follow the project page guidance.

Funding details

Fully funded PhD opportunity for 3 years.

What's required

Candidates should have a background in applied mathematics, computer science, computational biology, or a related field, and be interested in interdisciplinary research. The post does not specify language scores, GPA, or prior degree details beyond suitability for PhD-level research.

How to apply

Open the full description and application details via the provided link. Review the project page, then follow the application instructions there to submit your materials.

More information can be found here

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