The ANR Project HERELLES offers a two years Post-doctoral position
*/Interactive multi-paradigm collaborative learning for time series analysis/*
The post-doctoral project aims to propose an innovative method of interactive multi-paradigm collaborative learning, which combines supervised and non-supervised methods while allowing interaction with the expert.
The candidate will propose and define novel mechanisms that allow supervised and unsupervised methods to collaborate efficiently to reach a classification consensus. The modalities of information exchange between them will have to be specified. He/she will also have to define a protocol for interaction between the user and the learning methods through the use of constraints. Finally, he/she will have to concretely implement the proposed approaches to allow their testing and validation.
/Location/: Saclay (AgroParisTech campus, 22 place de l'Agronomie, 91120 Palaiseau) /(A location at Strasbourg can be discuted)/
/Duration/: One year (renewable once) – starting as soon as possible/Salary/: between 2500€ and 2700€ before taxes (brut) monthly according to past experience /Contact/: Antoine Cornuéjols antoine.cornuej...@agroparistech.fr and Pierre Gançarski, pierre.gancar...@unistra.fr
*EXPECTED PROFILE** * - PhD in Computer Science and specialized in Machine Learning/Data Mining.- Strong knowledge in Data Science and more particularly in standard classification and clustering methods. Experience in using collaborative/ensemble models or constraint integration would be a plus. - Good verbal (English or French) and written (English) communication skills. - Interpersonal skills and the ability to work individually or as part of a project team.
*TO APPLY*Send an email to antoine.cornuej...@agroparistech.fr <mailto:antoine.cornuej...@agroparistech.fr?subject=Application to post-doctoral position (HERELLES)> included curriculum vitae, list of publications, letter of motivation and contact details of three references. Applications will be accepted until the position is filled.
Sujet_HERELLES_(Eng)_2022.pdf
Description: Adobe PDF document
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