Jobs

Post-doc position

The chaire “Economie et gestion des nouvelles données” is recruiting a talented postdoc specialized in large scale computing and data processing. The targeted applications include machine learning, imaging sciences and finance. This is a unique opportunity to join a newly created research group between the best Parisian labs in applied mathematics and computer science (Paris­ Dauphine, INRIA, ENS Ulm, Ecole Polytechnique and ENSAE). The proposed position consists in working in the research of large­ scale data processing methods, and applying these methods on real­ life problems.
The successful candidate will integrate the Sierra INRIA team located at the new INRIA Paris center located in downtown Paris. He will benefit from a very stimulating working environment and all required computing resources. He will work in close interaction with the 4 research labs of the chaire, and will also have interactions with industrial partners.

A non­ exhaustive list of methods that are currently investigated by researchers of the group, and that will play a key role in the computational framework developed by the recruited post-doc, includes :
* Large scale non-­smooth optimization methods (proximal schemes, interior points, optimization on manifolds).
* Distributed optimization methods (asynchronous stochastic gradient optimization).
* Machine learning problems (kernelized methods, Lasso, collaborative filtering, deep learning, learning for graphs, learning for time­ dependent systems), with a particular focus on large­ scale problems and stochastic methods.
* Asynchronous parallel optimization methods.
* Imaging problems (compressed sensing, super­resolution).
* Hyperparameter optimization.

Candidate profile

The candidate should have a good background in computer science with various programming environments (e.g. Python and/or Matlab and/or Java/Scala) and knowledge of high performance computing methods (e.g. parallelization, GPU, cloud computing). He/she should adhere to the open source philosophy and possibly be able to interact with the relevant communities (e.g. Python, scikit-learn, Julia project, etc.). Typical curriculum includes PhD in computer science, applied mathematics, statistics or related fields.

The official language of the institute is english.

Application proces

Send a resume and a motivation letter to:
Alexandre d’Aspremont <aspremon@ens.fr>, Robin Ryder <ryder@ceremade.dauphine.fr>, Fabian Pedregosa <f@bianp.net>

For any questions please contact me at f@bianp.net .

 

Data science engineer position
Chaire Havas-Dauphine “Economie et gestion des nouvelles données”
● Location:INRIA Paris center located closely to Gare de Bercy.
● Duration: 1 year renewable at least once.
● Salary: highly competitive salary, to be discussed depending on the applicant’s profile.
● Start: as soon as possible.
● Application process: send a resume and a motivation letter to:
Alexandre d’Aspremont <aspremon@ens.fr>, Robin Ryder <ryder@ceremade.dauphine.fr>, Fabian Pedregosa <f@bianp.net>
Job description
The chaire “Economie et gestion des nouvelles données” is recruiting a talented engineer or postdoc specialized in large scale computing and data processing. The targeted applications include machine learning, imaging sciences and finance. This is a unique opportunity to join a newly created research group between the best Parisian labs in applied mathematics and computer science (Paris­ Dauphine, ENS Ulm, Ecole Polytechnique and ENSAE) working hand in hand with major industrial companies (AXA Global Direct, Havas, BNP Paribas). The proposed position consists in helping researchers of the group to develop and implement large­ scale data processing methods, and applying these methods on real­ life problems in collaboration with the industrial partners.
A non­ exhaustive list of methods that are currently investigated by researchers of the group, and that will play a key role in the computational framework developed by the recruited engineer, includes :
● Large scale non-­smooth optimization methods (proximal schemes, interior points, optimization on manifolds).
● Distributed optimization methods (asynchronous stochastic gradient optimization).
● Machine learning problems (kernelized methods, Lasso, collaborative filtering, deep learning, learning for graphs, learning for time­ dependent systems), with a particular focus on large­ scale problems and stochastic methods.
● Imaging problems (compressed sensing, super­resolution).
 Candidate profile
The candidate should have a good background in computer science with various programming environments (e.g. Python, Matlab, C++) and knowledge of high performance computing methods (e.g. parallelization, GPU, cloud computing). He/she should adhere to the open source philosophy and possibly be able to interact with the relevant communities (e.g. scikit-learn project). Typical curriculum includes engineering school or Master studies in computer science / applied maths / physics, and possibly a PhD (not required).
Working environment
The recruited post-doc will work within the new INRIA Paris center located closely to Gare de Bercy, in downtown Paris. He will integrate the SIERRA team and benefit from a very stimulating working environment and all required computing resources. He will work in close interaction with the 4 research labs of the chaire, and will also have regular meetings with the industrial partners.