Le post-doc proposé intervient dans le cadre d’un transfert technologique pour
une entreprise développant un assistant culinaire. Différents datasets de
recettes de cuisine ont récemment été rendus disponibles et permettent
l’apprentissage de réseaux de neurones profonds (voir par exemple [1]). Dans le
cadre de ce projet, on s’intéresse à proposer des aménagement de recettes de
cuisines suivant les ingrédients disponibles (réparation de recettes).
Le post-doctorant aura pour tâche
* Organiser différents jeux de données à des fin d’apprentissage
* Expérimenter, évaluer et combiner les architectures les plus pertinentes pour
un système de recommandation culinaire.
* Une ou plusieurs publications des travaux réalisés

Profil recherché pour le poste :
* Doctorat en Informatique
* Spécialisé dans le domaine de Deep Learning
* Familiarisé avec les frameworks les plus courants (keras, pytorch, tensorflow,
etc.)

Pour plus de détails : http://cazencott.info/dotclear/public/offers/2019-04-Postdoc-ANR.pdf

Centre for Computational Biology (CBIO):
The Centre for Computational Biology is part of Mines ParisTech, one of the major engineering schools for applied mathematics in France. Our research is dedicated to the development of methods and tools in the field of Machine Learning, Statistics and Computer Vision in order to analyze massive data generated in life sciences and medicine. We work on a broad range of applications, from questions in fundamental life science to precision medicine. The Centre for Computational Biology has a partnership with INSERM, the French national health institute, and the Institut Curie, a major hospital and research center dedicated to cancer. This partnership provides access to the infrastructure and facilities of the Institut Curie and facilitates collaborative projects with other groups at the Institut Curie, as well as data sharing. Our laboratory is located in the heart of Paris and we therefore benefit from an exceptional scientific and cultural environment.

Position summary:
We are seeking a senior scientist with several years of experience as an independent researcher and with an excellent track record in the fields of Machine Learning and Statistics applied to biology and/or medicine. In particular, we would like to consolidate our activity in the fields of genomics and analysis of next-generation sequencing data with applications both in fundamental biology and medicine. Any previous experience in these fields would be an advantage. The successful candidate is expected to work in a team of 4 permanent researchers on exciting questions in computational biology, to develop his/her own line of research for which (s)he will secure funding, to supervise PhD students and Postdocs and to contribute to the scientific animation in his field of research at the CBIO and the Institut Curie.

Application file:
The application should consist of the following documents:
– a cover letter;
– a detailed CV;
– a research project (5 pages limit);
– a list of publications and of oral communications at scientific conferences;
– three recommendation letters to be sent directly to the CBIO. Alternatively, the candidate can provide contact details for three referees to be contacted directly for recommendation;
– Copies of official transcripts for all degrees at all institutions attended.
Please send the documents before 06/06/2019, to Thomas Walter, by email (Thomas.walter@mines-paristech.fr), or by mail (CBIO, Mines ParisTech, 60 Boulevard Saint Michel, 75006 Paris).

Profil recherché : titulaire d’une thèse idéalement dans le domaine du Deep-Learning pour la Robotique ou le Véhicule Autonome (ou sinon, soit thèse en Deep-Learning appliqué à un autre domaine, soit thèse dans le domaine Perception ou Planification en Robotique ou Véhicule Autonome), et idéalement au moins une 1ere expérience post-thèse dans ces mêmes domaines [mais tenure-track juste après thèse aussi envisageable].

Pour + de détails sur le laboratoire, la fiche de poste et les modalités de candidature, voir la page ci-dessous :
http://caor-mines-paristech.fr/fr/2019/03/chargee-de-recherche-en-intelligence-artificielle-pour-la-robotique-et-les-vehicules-autonomes/

Description of the project and postdoctoral missions:

Social networks are regularly used to express opinions on public and political events or to disseminate opinions on sensitive topics (hate speech, hooliganism, racism and nationalism, etc.). The objective of the SAPhIRS project is to study opinion propagation within social networks: to identify the key mechanisms for disseminating information and opinion and to identify leaders of influence. Particularly in Security field, we will focus on Twitter detection and analysis of hamessages calling for hatred or violence, monitoring their spread and detection of influential actors.

As part of this project, we propose a 12-month postdoctoral position in machine learning for opinion mining, sentiment analysis and the detection of changes of opinion in Tweets. For this purpose, we plan to use state-of-the-art methods in NLP based on deep-learning neural networks, and especially recurrent neural networks with internal memory such as LSTMs or GRUs.

In other words, the main tasks would be:

To annotate tweets automatically according to an opinion: supervised classification problem;
To automatically identify messages containing the expression of radical ideas, in English, in French and in Arabic chat alphabet (transliteration of Arabic in Latin alphabet, also called arabizi or arabish): problem of supervised learning on unbalanced classes and possibly weakly supervised learning;
To detect changes of opinion in user Tweets sequences: detection of anomalies and breaks in a time series.

The main difficulties come from the encoding of input data (short texts from Twitter, in French and Arabizi) for which language models remain to be defined, and in the design and learning of adapted recurrent models dedicated to these three tasks.

Profiles:
Candidates must have a doctorate in Machine Learning with, if possible, experience in NLP and/or Deep Learning. Knowledge of recurrent networks and Arabizi would also be a plus.

Contractual conditions:
The contract will be 12 months starting as soon as possible, with a gross salary of approximately 3500 €. The recruited person will work in the LITIS lab at INSA Rouen Normandy in Saint-Etienne-du-Rouvray.

Application: CV, motivation letter, recommendation letters.