Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : CMLA / ENS Cachan
Durée : 12 à 36 mois
Contact : mlmda-jobs@cmla.ens-cachan.fr
Date limite de publication : 2016-05-31
Contexte :
In the context of people interacting with complex environments, various sensor technologies have been developed to record on-the-fly the responses of the human body. Such interactions include brain-stroke patients in rehabilitation process, neurological patients during clinical evaluations, operators monitoring industrial systems through SCADA, pilots in their cockpit, seniors in nursing houses, … It is a challenge of scientific and societal importance to organize, extract relevant information from the data collected and help decision-making along such interactions.
An interdisciplinary team of mathematicians, computer scientists, clinicians, and neurophysiologists involving two CNRS labs (CMLA and COGNAC G) and several hospital divisions has developed a methodology to implement a virtuous loop in which sensor signals feed structured databases on which state-of-the-art algorithms from signal processing and machine learning are executed to support interfaces for smooth observation, quantification and assessment by experts. This methodology aims at addressing key questions for clinical and ethomics research.
Sujet :
The candidates will participate in the protocol definition for data collection, data organization, functional data exploration, development of statistical methodologies for longitudinal follow-up and machine learning algorithms leading to operational prototypes tested in operational environments. Typical issues that arise along the projects are:
* Low-level signals processing and feature engineering
* Robust signal indexation and event detection
* Supervised and unsupervised machine learning algorithms, including multi-view learning
Profil du candidat :
Applications from candidates with top-notch scientific background with specific knowledge in data mining, data science, applied statistics, signal processing, or machine learning are welcome. Furthermore, technical and human qualities are also expected:
* Keen to interdisciplinary research and interaction
* Taste for numerical experimentation
* Interest for sensor technologies
* Desire to produce live demos and contribute to prototype solutions
* Creativity
* Excellent communication skills
* Strong programming skills
* Enjoy teamwork
Candidates should email a letter of application, a detailed CV including a complete list of publications, and source code showcasing programming skills to: Nicolas Vayatis (CMLA, ENS Cachan) < vayatis@cmla.ens-cachan.fr> and to
Formation et compétences requises :
Candidates with basic education in engineering sciences, applied mathematics, applied computer science or physics, and PhD in machine learning, data mining, statistical modeling, signal/image/video processing or computational medicine are welcome.
Adresse d’emploi :
Principalement :
CMLA – ENS Cachan
61, avenue du président Wilson
94230 Cachan
&
COGNAC G – Université Paris Descartes
45, rue des Saints-Pères
75006 Paris
Document attaché : postdoc-phd-position-at-cmla-2016.pdf