Offre en lien avec l’Action/le Réseau : – — –/– — –

Laboratoire/Entreprise : IRIMAS
Durée : 12 months
Contact : maxime.devanne@uha.fr
Date limite de publication : 2021-10-15

Contexte :
The volume of online sales in France is continuously increasing. Remote payments on the Internet concentrate most of the fraud on French credit cards (70% of the amount of fraud (255 M €) while it represents only 14% of the value of national transactions). Fraud is a complex phenomenon to detect. Indeed, fraudsters constantly adapt their techniques in order to outsmart the system, which poses a financial and reputational risk to e-commerce sites and banks.

Sujet :
The project aims to develop machine learning methods for the detection of credit card frauds. This project is a collaboration between the company Enygma, specializing in the detection of bank frauds, and the IRIMAS research institute specializing in machine learning methods.

Profil du candidat :
Applicants must have a PhD in Computer Science and demonstrate experience in the field of machine learning. We are looking for a profile with good experience in deep learning methods as well as programming in Python. Experience in optimization as well as CUDA programming would be a plus.

Formation et compétences requises :
Applicants must have a PhD in Computer Science and demonstrate experience in the field of machine learning. We are looking for a profile with good experience in deep learning methods as well as programming in Python. Experience in optimization as well as CUDA programming would be a plus.

Adresse d’emploi :
IRIMAS, Université de Haute-Alsace, Mulhouse
Gross Salary : 3250 €/month

Please contact Prof. Lhassane Idoumghar (lhassane.idoumghar@uha.fr), Dr. Jonathan Weber (jonathan.weber@uha.fr), Dr. Julien Lepagnot (julien.lepagnot@uha.fr) or Dr. Maxime Devanne (maxime.devanne@uha.fr) for more information about the position.

Document attaché : 202110081145_Post-Doc SATT Enygma Eng.pdf