Two Research Internships in Machine Learning and

**Two Research Internships in Machine Learning and Applied Mathematics - AI**: - Réf **ABG-127408** - Stage master 2 / Ingénieur- Durée 6 mois- Salaire net mensuel >500- 05/12/2024- Université Gustave Eiffel / IFSTTAR - Site de Marne-la-Vallée- Lieu de travail- Champs-sur-Marne Ile-de-France France- Champs scientifiques- Informatique - Mathématiques - Sciences de l’ingénieur - Mots clés- mathematical modelling, computer science, electrical, optimization, transportation, engineering, Vulnerability assessment, Disruption management, Battery-powered vehicle, energy storage, traffic simulation- - 31/01/2025**Établissement recruteur**: **Site web**: The Gustave Eiffel University is a **national multi-campus university**. It was created on 1 January 2020 as a result of the merger of the University of Paris-Est Marne la Vallée, Ifsttar, and several schools and engineering schools: EIVP, ENSG, ESIEE, and Ecole d'architecture Paris Est. **Gustave Eiffel University is Ranked 1st in Civil and Transportation engineering in France (ShanghaiRanking 2024)** and has more than 2,500 agents and 17,000 students at nine sites in France. The university hosts a quarter of the national research and development on sustainable cities and is home to the largest transport research center in Europe.It is a university on a human scale, bringing together multi-disciplinary skills that enable it to conduct quality research for the benefit of society, to offer training courses adapted to the socio-economic world, and to support changes in society and public policies. The GRETTIA research lab is part of Université Gustave Eiffel and carries out its research activity in the field of land transport systems. It is interested in all aspects of road and guided transport modes, from systemic aspects, modeling and simulation to the dynamic aspects of vehicles, including management, diagnosis and maintenance. GRETTIA contributes to the development of transport network and system engineering, taking into consideration the issues of integration, intermodality, reliability and system analysis. Within this framework, the research unit conducts a transversal activity of development of models and generic tools based on the field of mathematical engineering, advanced computer science and mechanics; contributes to the modeling, design, management,evaluation and maintenance of intelligent transport and infrastructure operation systems; studies the conditions of functional and social acceptability of new transport services. **Description**: **Starting date**: Flexible **In collaboration with UC Berkeley** **Location**: University Gustave Eiffel, COSYS department, GRETTIA Lab., 77420 Champs-sur-Marne, Paris area, France. **Role Description** **Project Overview**: This internship will place you at the forefront of a pioneering initiative aimed at resolving complex Traffic Network issues. The intricacies of solving mathematical problems stem from the need to model and determine the transportation network state under specific demand and supply conditions. Challenges include the diverse nature of network characteristics, the dynamic interplay of multiple Origin-Destinations (ODs), and the computational demand of existing methods. **Your Role**: The intern will be instrumental in developing an advanced framework for traffic network state analysis and prediction. You will: - Utilize ML methods to discern network dynamic evolution and contribute. - Employ deep learning and data mining to unravel the intricacies of mathematical problems. - Design and implement innovative algorithms, potentially involving generative Artificial Intelligence (AI) and attention mechanism models, to forecast optimal network states. **Research Tasks**: - Conduct a comprehensive literature review. - Learn to use existing ML algorithms and adapt them to our project's needs. - Process real-world data employing cutting-edge data mining techniques to inform the DNE model. - Develop and test the ML algorithms. - Validate the ML model against real-world scenarios to ensure accuracy and reliability. **Keywords**: Generative AI, transportation, machine learning, data mining, simulation, optimization, deep learning **Profil**: - Master level in the field of computer science and applied mathematics. - Experience in Pattern Recognition, Neural Networks, and Transformers. - Solid skill in computer programming Python, data analysis, mathematical modeling and optimization, and Basic knowledge of game theory and graphs. - Good level of English (reading and writing). - Strong analytical and problem-solving skills - Ability to work independently and as part of a team **Prise de fonction**: - Dès que possible