Ph.D position in Health Economics and Network Analysis (M/F)

Job Description

Thesis Subject

Healthcare workers' quality of working life (QWL) is a central determinant of hospital performance, care continuity, and professional retention — particularly in emergency departments (EDs), where structural unpredictability, high decisional pressure, and intense workloads create challenging conditions. Despite a growing body of literature on burnout, absenteeism, and turnover, existing research rarely connects the actual structure of professional interactions with working conditions, and largely overlooks temporal dynamics and medical complexity.
The NEOS project addresses these gaps by developing an innovative and integrative framework combining health economics, network analysis, and time-series econometrics, applied to large-scale hospital data from the PREDIMED health data warehouse of the CHU Grenoble Alpes. This project covers the period 2020–2025, capturing major organizational transformations — including internal restructuring of ED teams and the closure of peripheral emergency units — that provide a unique quasi-experimental setting. Regulatory clearances from the CNIL and CESREES have already been obtained for the 2020–2022 period, and an extension request covering 2023–2025 is currently under review.
The PhD candidate will construct continuous, objective indicators of workload and stress from administrative and clinical data, model their temporal dynamics using time-series methods (SARIMA, VAR, interrupted time series), and analyze professional collaboration networks weighted by medical case complexity. The project will also mobilize advanced network models (TERGM, SAOM) to study the creation and dissolution of professional ties over time, and their relationship with workload and stress indicators. Organizational shocks will be studied using structural break detection and quasi-experimental approaches, providing robust causal evidence on the effects of hospital reorganizations on collective work sustainability.

Profile and skills
Required
• Master's degree in economics, applied econometrics, statistics, or a related quantitative field
• Strong background in time-series econometrics
• Proficiency in R programming
• Interest in interdisciplinary research and health-related topics
Appreciated
• Familiarity with social network analysis
• Experience with large-scale administrative or health data
• Reading proficiency in French (data and institutional context are French)

Documents to be submitted with your application:
• A cover letter outlining your interest in the role and your qualifications
• A CV

Your Work Environment

This thesis will be co-supervised by Carole Treibich (GAEL, health economics and network data analysis) and Joris Giai (MCU-PH in public health, TIMC laboratory, head of the export department at the PREDIMED health data warehouse), ensuring strong interdisciplinary supervision at the interface of economics, data science, and clinical medicine.
Resources provided: a computer, a desk and support staff.

Compensation and benefits

Compensation

2300 € gross monthly

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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