- Extract features from network traffic data format (pcap and IPFIX) including temporal features and encrypted-specific features
- Extract meta behavioral feature from graph representation of the network activity
- Distance and similarity metrics over defined features
- Embeddings as fixed size vector of extracted feature to remove categorical dat
- Specification of the software architecture
- Identification of features to BE extracted through interaction with the research team
- Identification of existing tools to BE reused
- Specification and developing modules to extract data from raw data files
- Specification and developing modules to extract knowledge from data and metrics or embedding from the constructed representation (vectors, graphs, timeseries)
- Integration of research work supporting autoconfiguration of ML algorithms
- Maintaining the developer documentation and user guide
- Preparing and presenting tutorials, demos and hackathon in the RESIST team and for international venues (scientific conferences)
- Providing support to the beta tester (the team)
- Required knowledge : networking, machine learning and their relative tools (wireshark, scikit learn, pandas, dask)
- Languages : Shell, python and others are appreciated
- Software developement : continuous integration and collaborative development using gitlab
- Fluent in engish (writing and oral communication)
- Comfortable with meetings and webconference situations
- Partial reimbursement of public transport costs
- Leave : 7 weeks of annual leave + 10 extra days off due to RTT
- Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage
-
Phd Position F
il y a 3 semaines
INRIA VILLERS LES NANCY, FranceJob details · Job Type · Temporary · Contract · Full Job DescriptionLe descriptif de l'offre ci-dessous est en Anglais · Type de contrat : CDD · Niveau de diplôme exigé : Bac +5 ou équivalent · Fonction : Doctorant · Contexte et atouts du poste · The PhD position is proposed by t ...
-
PhD Position F/M Collaboration over a distributed file system
il y a 1 semaine
INRIA Villers-lès-Nancy, France CDDContexte et atouts du poste · This PhD thesis will take place in team COAST, under the supervision of Claudia-Lavinia Ignat, HDR, CRCN Inria, Inria center of Lorraine University and Gérald Oster, MCF, Lorraine University · Mission confiée · File system services are essential fo ...
-
INRIA Villers-lès-Nancy, France CDDContexte et atouts du poste · This PhD thesis will take place in team COAST and will be supervised by Claudia-Lavinia Ignat, HDR, CRCN Inria, Inria center of Lorraine University and Olivier Perrin, Professor, Lorraine University. · Mission confiée · We want to propose a securi ...
-
INRIA Villers-lès-Nancy, France CDDContexte et atouts du poste · This PhD thesis will be supervised by Claudia-Lavinia Ignat, researcher at Inria center of Lorraine University and co-supervised by Léo Joubert, assistant professor at Université de Rouen Normandie. · Mission confiée · Large-scale collaborative sys ...
-
Desktop Support Specialist
il y a 1 jour
Microland Limited Custines, FranceExciting Career Opportunity · Designation - Onsite IT Support Engineer · Hiring Immediately · ★ Onsite Work - Monday to Friday · ★ No Remote Work - % Onsite · Microland is a Digital Accelerator. It provides enterprises the means to adopt and consume NextGen technologies in their ...
-
Research Engineer in Direct Reduction
il y a 2 semaines
Science me Up Metz, FranceOBSERVABLE UNIVERSE OF THE COMPANY · Our client, a world's leading steel and mining company, is looking for a Research Engineer in Direct Reduction. · Steel industry accounts for some 7-9% of global carbon emissions today. Iron ore reduction is where the vast majority of carbon e ...
Engineer Position on Developing An Open-Source Machine Learning Toolbox For Network Analytics H/F - VILLERS LES NANCY, France - INRIA
![Default job background](https://contents.bebee.com/public/img/bg-user-ex-1.jpg)
Description
Job detailsJob Type
Temporary
Contract
Full Job DescriptionLe descriptif de l'offre ci-dessous est en Anglais
Type de contrat :
CDD
Niveau de diplôme exigé :
Bac +5 ou équivalent
Fonction :
Ingénieur scientifique contractuel
Contexte et atouts du poste
Team
This position is proposed by the RESIST team of the Inria Nancy Grand Est research lab, the French national public institute dedicated to research in digital Science and technology.
The team has strong research records in designing new methods and developing tools based on machine learning algorithms to manage networks.
fingerprinting user actions on IoT devices, detection of anomalous behavior in encrypted TLS communications, analysis of large darknet
The team is actually one of the European research group in network management and is particularly focused on empowering scalability and security of networked systems through a strong coupling between monitoring, analytics and network orchestration.
About 30 members are in the team, that include permanent researchers, professors, PhD students and engineers working on various topics (artificial intelligence applied to network management, programmable dataplanes, virtualization of networks, security monitoring)
The team is part of LORIA which is a joint lab between INRIA, University of Lorraine and CNRS.
IT provides a full ecosystem to support highly innovative research and development with more than 400 people in total within a larger scientific campus of Nancy.
ContactsJérôme François (jerome dot francois at inria dot fr) and Frederic Beck (frederic dot beck at inria dot fr)
Mission confiée
Project overvview
During the last twenty years, there has been an increasing adoption of advanced analytics techniques, especially Machine Learning (ML), in all areas of networking developed to achieve a higher level of automation with the key objectives being to extract relevant information from observations in order to reach different goals such as enhancing performance or end-user experience, lowering the carbon footprint or improving network security.
With the exponential increase of the use and adoption of ML techniques in the last decade, tools to support ML have reached a high maturity level including scikit-learn, orange, keras, dask, etc.
Historical communities in image or speech processing have been able to produce and standardize techniques and open-source tools available for all.
Although network community is now both a user and a provider of techniques to support the use of ML, a very few techniques have been community-wide adopted or standardized and the main trend is to redefine and redevelop similar techniques for each use.
Therefore, our ambition is to support and lead a similar effort in our scientific community, networking and network management, with as a final goal the development of an extensible ML toolbox for networks.
Activities
The objective is to create a first version of the toolbox which must BE extensible and re-configurable.
Indeed, as a starting point we will focus on the initial steps of ML pipeline that encompasses data ingestion, data pre-processing to represent data as graphs or vectors and feature extraction.
The toolbox will BE open-source and must BE interfaced with other existing tools as for example scikit-learn.The initial version of the library will have the following expected functionalities :
The engineer will have to directly interact with all team members to derive the requirement of such a library keeping in mind that the goal is to make this library accessible to everybody, even to non members (open-source project).
The tasks of the engineer will BE :
According to profile