|CDI, Palaiseau, France.|
|Entreprise/Organisme :||Ecole polytechnique, Institut polytechnique de Paris|
|Niveau d'études :||Autre|
|Date de début :||September, 1st, 2022|
|Secteur d'activité :||Academia|
|Description :||Ecole polytechnique is recruiting an Associate Professor in Statistical Learning, starting on 2022 September 1st.
We are looking for candidates with more than 5 years of international experience after his/her PhD.The candidate must demonstrate contributions in the field of machine learning/statistics/applied probabilities at the highest international level. The excellence of these contributions should be evidenced by publications in the best journals (Annals of Statistics, Electronic J. Statistics, Annals of Applied Probability, Annales Institut H. Poincaré, Bernoulli, J. Machine Learning Research, Stochastic Processes and their Applications, etc) and/or international conferences (NeurIPS, ICML, COLT, AISTAT, ICLR, ALT, etc). We place great emphasis on the applicant's ability to work in a team and interact with CMAP faculty and researchers in MachineLearning/Statistics/Applied Probability.
The candidate will conduct his/her research at CMAP within the “Signal IMage Probabilités numériques Apprentissage Statistique” (SIMPAS) team and within the Interdisciplinary Research Center for Data Science and Artificial Intelligence Hi!PARIS. The candidate must submit a detailed scientific project showing how his/her research will strengthen Ecole polytechnique (he/she is strongly encouraged to contact the team to discuss his/her research project).
ThecandidatewillbeinvolvedinthepedagogicalcoordinationoftheX-HECMsCT"Data-ScienceforBusiness" in conjunction with the current coordinator, and will be able to contribute to the teaching of statistics, applied probability, optimization and machine learning. He/she will participate in teaching at all levels of education (bachelor degree, engineer degree, master's degree in applied mathematics and statistics, executive education). The ability to propose innovative pedagogical initiatives adapted to the different target groups we train will be highly appreciated. In particular, the applicant's ability to contribute to project-based teaching and to strengthen the links between teaching, research and applications will be an important point.
Ecole Polytechnique offers an exceptional teaching and research environment. Research and teaching benefit from the scientific, administrative and budgetary support of the CMAP and the DMAP department.
For further information, candidates may contact Eric Moulines, Professor (email@example.com) or Gersende Fort, Part-time Professor (firstname.lastname@example.org).|
|En savoir plus :||https://gargantua.polytechnique.fr/siatel-web/app/linkto/mICYYYShuYS|