Postdoctoral Position in Neuroscience and Machine Learning (M/F)

Job Description

Missions

You will join an interdisciplinary team at CNRS to work on an innovative project aimed at:
• Building a preclinical database using murine models (mice/rats) to study the impact of respiratory neuromuscular stimulation.
• Developing predictive models (supervised/unsupervised learning, deep learning) to identify responders/non-responders and optimize stimulation programs.
• Validating models through experimental protocols on animals, combining biology, signal processing, and data science.

Activity

The project is structured around two main axes:
1. Animal Experimentation: Acquisition of physiological data (EMG, respiration, SpO2, etc.) from murine models.
2. Predictive Modeling: Development of advanced machine learning methods to analyze this data and propose optimal stimulation programs.

Main Responsibilities:

1. Animal Experimentation (30 à 40% of time)
• Design and implementation of protocols on murine models:
o Measurements at D0, D2, D3, D15: weight, respiratory parameters (Vt, Fr, Ti, Te), EMG (diaphragm/intercostal/abdominal), SpO2, lean mass index, respiratory variability.
o Compliance with good practices (ethics, regulations on animal experimentation).

• Data acquisition and preprocessing:
o Cleaning, structuring, and annotating data to make it usable for machine learning.
o Automation of data collection pipelines (Python scripts).

2. Predictive Modeling (60 à 70% of time)
• Development of supervised and unsupervised learning models:
o Classification (SVM, Random Forest, KNN) to predict response to stimulation.
o Regression to estimate the effectiveness of stimulation programs.

• Application of deep learning methods:
o Use of neural networks (CNN, possibly RNN/Transformers) to analyze biological signals (EMG, respiration).
o Integration of multimodality (combining numerical data and raw signals).

• Statistical processing and biological data modeling:
o Analysis of signal variability (ECG, EEG, EMG).
o Selection of relevant features and model interpretability (SHAP, LIME).

• Model validation:
o Performance evaluation (AUC-ROC, precision/recall, RMSE).

Your Profil

Skills

🔹 Mandatory Skills in Neuroscience and Modeling
• Experience in developing supervised and unsupervised learning methods:
o Mastery of classification algorithms (SVM, Random Forest, KNN) and regression.
o Experience in feature selection and model validation.
• Knowledge of deep learning methods:
o Experience with CNNs (for signal analysis) and possibly other architectures (RNN, Transformers).
o Ability to adapt these methods to complex biological data.

• Knowledge of biological data in signal theory:
o Experience with physiological signals (ECG, EEG, EMG): acquisition, preprocessing, feature extraction.
o Understanding of specific challenges related to the analysis of these signals (noise, artifacts, inter-individual variability).

• Knowledge of statistical processing and biological data modeling:
o Mastery of statistical tests (ANOVA, regression, non-parametric tests).
o Experience in predictive modeling applied to biology or medicine.

🔹 Mandatory Skills in Animal Experimentation
• Proven experience in handling murine models (mice/rats):
o Knowledge of neuromuscular stimulation protocols.
o Mastery of physiological data acquisition techniques (EMG, respiration, SpO2).

• Compliance with ethical and regulatory standards related to animal experimentation.

🔹 Computer Development Skills
• Confirmed experience in Python:
o Mastery of libraries: scikit-learn, tensorflow/pytorch, pandas, numpy, matplotlib/seaborn.
o Ability to develop robust scripts for preprocessing, analysis, and modeling.

• Use of collaborative tools:
o Git (version control), Jupyter Notebooks, development environments (VS Code, etc.).

Your Work Environment

NeAR Team, Environment: 9 Principal Investigator researchers, 5 PhD students, 3 study engineers; a specific respiratory research group composed of 3 PhD students and 1 study engineer. Shared experimental areas, teamwork highly valued, weekly working meetings, and weekly lab and/or unit seminars.

Constraints and risks

The position involves risks related to animal experimentation (handling murine models, injections, sampling) as well as the use of chemical products for immunohistochemistry and biochemistry (reagents, stains, solvents). The candidate must comply with current safety protocols (wearing personal protective equipment, handling under a laminar flow hood when necessary) and adhere to regulations regarding animal ethics and chemical waste management. Training in laboratory best practices will be provided upon arrival.

Compensation and benefits

Compensation

According to CNRS scale (approximately €3,200–4,000 gross/month)

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

The research professions