Associate Professor in “Machine-Learning for Big Data”
The group dedicated to Research in Statistics (the research group STA), within the Signal & Image processing department (the TSI Dpt.), is recruiting an Associate Professor in the domain of machine-learning. All fields related to machine-learning are of interest for the team and a specialization in Machine-Learning for Big Data, focusing on scalable, parallel/distributed and on-line algorithms, will be favorably considered. Graph-mining, reinforcement learning and optimization are other topics of special interest for the group.
• Academic research programs in machine-learning will be carried out.
• Research results will be published in leading journals and conferences. Activities in scientific bodies, organization of special sessions, workshops as well as involvements in committees of scientific conferences will contribute to the visibility.
• The research activities will rely on the team expertise, which covers both theoretical and methodological works in Bayesian estimation, statistical learning, reinforcement learning, and distributed statistics with collaborative computing.
• Contributing to scientific projects involving industrial partners will be done by participating to bilateral contracts, proposals to national and international research project calls, in the context of an industrial chair dedicated to Machine-Learning or by co-supervising PhD theses (including CIFRE theses, involving industrial partners). The current applications considered within the group often deal with signal processing applications, which encompass forecasting, design of computer experiments, source separation, localization/tracking/cartography, control in multi-agent system.
• In the domain of statistics and machine-learning, teaching at Telecom ParisTech mainly occurs at the level of bachelor or master courses (e.g. probability, statistics, optimization), as well as in specialized training courses (e.g. machine-learning). The master courses include courses in joint masters with partner universities, such as MVA Master (Mathematics, Vision and Learning) at ENS Cachan, as well as courses in a novel professional master of Telecom ParisTech fully dedicated to Big Data (“Management and Analysis of Big Data”). The candidate will participate to these teaching activities.
• Education : PhD or equivalent
• An international postdoctoral experience is welcome but not mandatory
• English: fluent; French: good or the candidate should be willing to improve it
Knowledge and experience required
• Research publications in machine-learning
• Teaching experience at the university level
• Knowledge on techniques in machine-learning, which permit to handle “Big/Complex Data”, e.g. scalability, on-line algorithms running in the context of parallel and cloud architectures, graph-mining, large-scale programming (Hadoop MapReduce).
• Experience of Big Data applications in science or industry (e.g. recommender systems, collaborative filtering, social networks analysis, computational advertising, behavioral targeting)
• Theoretical or practical knowledge in optimization.
• Theoretical or practical knowledge in reinforcement learning
Other Qualities and skills
• Capacity to work in a team and develop good relationships with colleagues and peers
• Good writing and pedagogical skills
In the context of the Paris Saclay University, activities in stochastic modeling and statistical data processing at the STA group are part of the Labex Hadamard (Mathematics and Applies Mathematics) and of the Labex DigiCosme (Digital worlds: distributed data, programs and architectures) both at the same time. The research activity of the candidate should permit to build up effective collaborations with the IC2 group (databases, visualization and interfaces) of the Computed Science Department of Telecom ParisTech.
• Permanent position
• Place of work: Paris until 2017, and then Saclay (Paris outskirt)
• For more info on being an Associate Professor at Telecom ParisTech (in French)
Application can be performed electronically by electronic mailing to
Application should include :
• A complete and detailed curriculum vitae
• A letter of motivation,
• A document detailing past activities of the candidate in Teaching and Research: the two types of activities will be described with the same level of detail and rigor.
• The text of the main publications,
• The names and addresses of two references,
• A short teaching project and a research project (maximum 3 pages)
• June 5, 2013: application deadline
• Late June orearly July, 2013: interviews (by visio-conference eventually)
• Fall 2013: beginning
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