Organisation/Company Université de Caen Normandie Research Field Neurosciences Researcher Profile Recognised Researcher (R2) Positions Other Positions Country France Application Deadline 15 Dec 2024 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Mar 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? NoOffer DescriptionProject contextFunctional MRI in the resting state could be a valuable tool for the early diagnosis of certain brain pathologies. However, its accuracy is limited by the existence of a number of confounding factors, such as drowsiness. Recent studies suggest that drowsiness can significantly affect measures of brain connectivity. In addition, the use of different correction techniques may result in variable cognitive messages. Unfortunately, the conditions of the resting-state fMRI examination can induce drowsiness, making it difficult to use this test for personalised medicine. Following preliminary work, the project aims to develop a new brain imaging toolbox based on a machine learning approach to detect drowsiness during resting fMRI in order to improve its sensitivity and specificity. This tool will be evaluated on a large cohort of patients, in particular for medical monitoring purposes. The project will adopt two approaches to take account of these constraints: (I) Development of a drowsiness classifier based on physiological time series (such as cardiorespiratory variations), making it possible to detect states of drowsiness during MRI. (II) Development of a classifier based solely on the resting fMRI signal. This classifier will be based on the analysis of dynamic transitions observed in brain graphs between wakefulness and the first phases of sleep.MissionsThis project requires a large multimodal database combining resting-state fMRI signals, feature vectors for classifier development and ground truth constructed by experts. For this project, we will build a mixed database including previous acquisitions and a complete multimodal dataset acquired specifically for this project. The research engineer recruited will be responsible for setting up and managing this database, while ensuring the quality and conformity of the observations.Where to applyE-mail ****** Field Neurosciences Education Level PhD or equivalentSkills/QualificationsPhD in neuroscience, biomedical engineering, or related field, with a specialisation in data analysis and database development.Experience in processing multimodal data (fMRI, EEG, video, physiological data) and developing classification algorithms for neuroscientific applications.Competence in dynamic functional connectivity analysis and methodologies for correcting physiological effects on fMRI signals.#J-18808-Ljbffr