The Laboratoire d’Informatique de Paris 6 (LIP6) in Paris has a two-years funded full-time Post-Doctoral Researcher position available in machine learning.
The position takes place within a project with industrial (Salezeo and Synthesio) and academic partners (CNRS/LIMSI lab in Orsay and HEC Paris). The successful candidate will have to develop original techniques for representation learning, able to deal with heterogenous multi-relational and dynamic graphs, in the context of a recommandation task. The difficulty is to integrate various sources of heterogeneous of dynamic information (text, micro-blogs, semantic and structured information, social networks) of a large number of evolving entities, and to use this representation to solve recommandation tasks. This research will benefit from a stream of data and feedback, allowing to develop and experiment original solutions.
The successful candidate will join the machine learning and information access team of the University Pierre et Marie Curie, Paris, France, led by Prof. Patrick Gallinari. The post-doc will be supervised by Prof. Patrick Gallinari and Dr. Benjamin Piwowarski. Our research explores a number of different issues such as: representation learning for relational and dynamic data, reinforcement learning, deep neural networks. The University Pierre et Marie Curie is referenced as the first French university in the academic ranking of international universities.
Location: LIP6, University Pierre et Marie Curie, Paris (France)
Duration: April 2015 – March 2017 (2 years)
Net salary: from 1,800 Euros to 2,400 Euros per month, commensurate with experience.
The ideal candidate will have:
- A PhD in machine learning, data mining or other strongly related discipline
- A very solid background in computer science and mathematics. Special areas of interest include: statistical machine learning, representation learning.
- Strong publication record in the area of machine learning.
- Solid programming skills to conduct experiments
- Excellent command of English and team work capacity.
Candidates should send to Patrick Gallinari and Benjamin Piwowarski:
- List item
- a CV
- a cover letter explaining why their skills, knowledge and experience make them a particularly suitable candidate for the given position
- Their three most representative papers
- The name and emails of two referees