Assistant Professor, Machine learning, data sciences, data mining, statistics

Short Description:
Tenured faculty at the level of assistant-professor level (09/2015), in the domain of applied mathematics, with  emphasis in one of the following areas: statistics, theoretical machine learning, data mining.

Research fields:
Statistics, theoretical machine learning, data mining, kernel methods, multi-task learning.

Research :
The selected candidate should have an exceptional theoretical research background in one of the following fields: applied statistics and/or machine learning and/or data mining and/or data sciences.

He is expected to develop a new research group in one of the above respected fields targeting the development of novel theoretical method along with their application to different domains. His research will be carried out at the Data Sciences, Machine Learning and Visual Computing Center (in collaboration with Inria), an interdisciplinary and highly competitive environment at the intersection of applied mathematics, computer science and statistics.

Particular emphasis should be given to course analytics as an application domain or in other data science domains (biology, visual computing, bio-informatics, recommendation systems).

The selected candidate should have a PhD in one of the above fields and proven track record of excellence with publications to the top level international conference and journals of his field as well ability to carry on independent and highly ambitious research agenda both in terms of theoretical contributions as well as in terms of their application to societal challenges of the decade to come.

Teaching :
The selected candidate will provide his teaching in the department of Mathematics, under the steering of the director of department. He will teach primarily in the field of Statistics, as well as relevant fields depending on the school needs (probabilities, machine learning, data mining, etc).

More precisely, he will be in charge of the Advanced Statistics course (M.Sc. level), proposed in the second-year of the Engineering program. Progressively he should be involved on the Foundations of Statistics course (mandatory course of the engineering program). He could also be involved in tutorials of other first-year courses of Mathematics, especially the Real Analysis and Probability courses.

Depending on the needs, the selected candidate may be involved in the teaching in third-year Applied Mathematics program. He may also supervise research projects of second-year students.

Application deadline: 15/05/2015
How to apply (through e-mail,
To:erick.herbin@centralesupelec.fr, nikos.paragios@ecp.fr
Subject: Assistant Position CVN/CentraleSupelec):

  • full resume
  • 3-page research/teaching statement
  • ¬† list of three references