Postdoctoral position in LIP6 - Time-dependant topic models

The Laboratoire d’Informatique de Paris 6 (LIP6) in Paris, France, has a 12 months funded full-time Post-Doctoral Researcher position available in machine learning. The main topic is to learn time-dependent topic and word representations for large scientific document collections.
The position takes place in the context of the EPIQUE project, which aims at building phylomemies (graphs of time-dependent topics). One particular goal is to leverage work conducted on latent topic models, and especially temporal adaptation of those. The focus will be on developing and implementing word/topic representation-based models.
The ideal candidate will have:
- A PhD in machine learning, data mining or other strongly related data science topics.
- A very solid background in computer science and mathematics. Special areas of interest include: topic models, deep learning, big data processing and optimization.
- Strong publication record in the area of machine learning and data science.
- Solid programming skills (Python, one or more ML frameworks, Java/Scala) to conduct experiments
- Excellent command of English and team work capacity.
The successful candidate will join the Database team of the DAPA department, University Pierre et Marie Curie, Paris, France, led by Prof. Bernd Amann. The candidate will have strong interactions with the MLIA team (Machine Learning and Information Access team) of the DAPA department, and will be supervised by Prof. Bernd Amann and Dr. Benjamin Piwowarski. 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)
Start: Before July 2018
Duration: 1 year
Net salary (indicative range): from 1,800 Euros to 2,400 Euros per month, commensurate with experience.
Candidates should send to benjamin.piwowarski-AT-lip6.fr and bernd.amann-AT-lip6.fr :
- a CV
- a short text 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