PhD Position F/M Statistical methods for meta-model integration in pharmacology

TN France; Paris; Hybride; EUR 30 000 - 50 000; Plein temps

Résumé du poste

An innovative research opportunity awaits a PhD candidate in the vibrant city of Paris, focusing on integrating multiscale models in pharmacology. This role is pivotal in creating digital twins for personalized medicine, allowing for the exploration of treatment strategies tailored to individual patients. The position offers a collaborative environment with leading experts, where you'll engage in cutting-edge research, publish findings, and present at conferences. Enjoy a flexible work schedule, generous leave, and reimbursement for public transport costs, making this a compelling opportunity for aspiring researchers in the field.

Prestations

Partial reimbursement of public transport costs

Seven weeks of annual leave

10 extra days off due to RTT

Possibility of teleworking

Flexible working hours

Provision of professional equipment

Social, cultural, and sports events

Qualifications

• PhD candidates must have a strong background in biostatistics or related fields.
• Experience in R or Python coding is essential for this role.

Responsabilités

• Integrate multiscale and longitudinal meta-models for pharmacological digital twins.
• Check coherence of meta-models and estimate patient trajectories.

Connaissances

Biostatistics

Statistics

Mathematics

R coding

Python coding

English proficiency

Formation

PhD in Pharmacology or related field

Description du poste

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PhD Position F/M Statistical methods for meta-model integration in pharmacology, Paris

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Client:

INRIA

Location:

Paris, France

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

d217c6e6c840

Job Views:

1

Posted:

03.05.2025

Expiry Date:

17.06.2025

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Job Description:

The PhD will be funded by the Governmental Acceleration Funding - PEPR Santé Numérique. The candidate will work with all partners of the PEPR DIGPHAT project.

Context:

Pharmacology inherently requires modelling mechanisms across various scales: molecular (identifying drug action mechanisms), cellular (e.g., characterizing tissue lesions and biomarkers), and patient (pharmacokinetics/pharmacodynamics population variability). Notably, all these models are fundamentally longitudinal. Integrating these multiple scales is crucial to individualize treatments, including drug selection, optimal dosage, and associated regimens.

Despite the development of mechanistic models (such as those utilizing differential equations) at each scale by different research communities, there is still a lack of interoperability. Combining all relevant meta-models (each representing its own scale) will create a comprehensive digital pharmacology twin.

Objectives:

To propose a general pathway towards pharmacological digital twins by integrating several multiscale and longitudinal meta-models. Digital twins that enable the a priori investigation of a treatment strategy and the dynamic assessment of the probability of success based on a patient’s longitudinal features.

Main activities:

• Checking the coherence of meta-models at the same level.
• Chaining meta-models across different scales.
• Estimating new patient trajectories.

Additional activities:

• Writing articles
• Presenting talks and posters at conferences
• Specialization in Biostatistics, Statistics or Mathematics
• R or Python coding skills
• Good English level appreciated

Advantages:

• Partial reimbursement of public transport costs
• Seven weeks of annual leave plus 10 extra days off due to RTT (statutory reduction in working hours) and the possibility of exceptional leave (e.g., for sick children, moving home)
• Possibility of teleworking
• Flexible organization of working hours after 12 months of employment
• Provision of professional equipment (videoconferencing, loan of computer equipment, etc.)
• Social, cultural, and sports events and activities