Past offers

Maintenance d'une plateforme de GPUs pour le deep learning
  • Buts:
    • Maintenance d'une plateforme de GPUs (du cluster, du système de gestion des jobs, et des logiciels)
    • Création d'une plateforme expérimentale commune (benchmarks, bibliothèque commune recensant les modèles de réseaux de neurones des utilisateurs, animation: tutoriels, dissémination du code)
  • Contexte: groupe de travail GT Deep Net, de Digicosme
  • Lieux: LIMSI / IDRIS / LRI (Université Paris-Sud)
  • Détails: description du poste
  • Contacts: Alexandre Allauzen (allauzen at limsi dot fr) et Guillaume Charpiat (guillaume dot charpiat at inria dot fr)

Scientific Territory and Maps: the Cartolabe project
  • Goal: Build a visual representation of a scientist network, based on their publications (HAL papers and meta-data), using existing open source tools. The main intended functionalities include:
    • Visualizing the sub-network relevant to a (full text) query
    • Visualizing the temporal evolution of a person, a lab, a field.. scientific activity
  • Where: at TAO , the Machine Learning and Optimization team at INRIA - CNRS - Univ. Paris-Sud
  • Profile: The successful candidate should hold an Engineer Diploma (2014 or 2015) in Computer Science, be proficient in Python or Java languages, skilled in Web programming languages (Javascript, HTML5), with good knowledge of online database management. Basic knowledge in machine learning, data mining and/or data visualization is a plus.
  • When: Starting December 2015
  • Duration: 2 years
  • Contact: Philippe Caillou (caillou at lri dot fr) and Michele Sebag (sebag at lri dot fr)

Contributors to this page: evomarc , guillaume , sebag , caillou , Olivier and rros .
Page last modified on Thursday 19 of December, 2019 08:39:44 CET by evomarc.