Internships in Data Science

3D Computer Vision - Samp

SAMP - Raiselab, 11eme Paris

Large Language Models

LIG, Grenoble

Brain-based learning networks

NeuroMod Institute, Sofia Antipolis

Apprentissage fédéré

BioMérieux, Grenoble ou Lyon

Video Tracking

TDK, Grenoble

Full Stack Dev Junior

EdenIA, Lyon

Optimisation de Placement Multi-Marchés

Supergrid, Saint-Martin D’Hères

Structural Optimization

ANSYS, Lyon/Paris

Travelling with turtles

LJK, Grenoble

Various offers

CEA, Grenoble

Internships in MSCI

Modélisation numérique d’écoulements astrophysiques

Laboratoire J.A. Dieudonné, Nice (France)

3D Instance Segmentation

ENPC, France, SAMP - Raiselab, 11eme Paris

Analyse des dynamiques d’un système Zooplancton-Algues-Virus

Plant Genome and Development Laboratory, Perpignan

Geometric Statistics

Laboratoire J.A. Dieudonné, Nice

Etude CFD d’ébullition en film

CEA, Cadarache, France

Méthodes numériques pour le roulage stationnaire

INSA, Lyon et Michelin, Clermont-Ferrand

Sparse Control

CRAN, Nancy

Video Tracking

TDK, Grenoble

Traitement d’image

G-SCOP, Grenoble

Sensor simulator

TDK, Grenoble

Maillage volumique

Dassault System, Vélizy-Villacoublay

An introduction to shape and topology optimization

In a very broad acceptation, shape and topology optimization is about finding the best domain (which may represent, depending on applications, a mechanical structure, a fluid channel,…) with respect to a given performance criterion (e.g. robustness, weight, etc.), under some constraints (e.g. of a geometric nature).

Computational biology

This interdisciplinary course is designed for students with a computer science or mathematical background, offering them an opening to bioinformatics and to bioinformatics and computational biology.

Differential Calculus, Wavelets and Applications

The course is structured in two parts, treated respectively and independently by Sylvein Meignen and Kévin Polisano. The first part is devoted to differential calculus and its applications in image restoration and edge detection. The second part is dedicated to the construction and practical use of the wavelet transform. Wavelets are basis functions widely used in a large variety of fields: signal and image processing, data compression, smoothing/denoising data, numerical schemes for partial differential equations, scientific visualization, etc. Connections between the two parts will be made on the aspects of denoising, edge detection and graph analysis.

Efficient methods in optimization

Theoretical foundations of convex optimization.

Fluid mechanics and granular matter

Equations and models are presented in a continuum setting, and then approximated in time and space. Then, the efficient numerical resolution is addressed with some examples of practical applications.

Geophysical imaging

In the current context of energy transition and fight against global warming, a precise knowledge of the crust, down to several km depth, has become a critical issue.

GPU Computing

In this course, we will introduce parallel programming paradigms to the students in the context of applied mathematics.

Handling uncertainties in (large-scale) numerical models

Numerical simulation is ubiquitous in today’s world. Initially confined to well-mastered physical problems, it has spread to all fields (oceanography, biology, ecology, etc.), the aim being to make forecasts of the systems under study.

Modeling Seminar

This lecture proposes modelling problems. The problems can be industrial or academic.

Méthodes de calage de paramètres en temps réel.

Méthodes de calage de paramètres en temps réel.

Optimal transport: theory, applications and related numerical methods.

The goal of this course is to present a wide range of recent numerical methods and algorithms that find applications in various fields. More precisely, the course will focus on optimal transport algorithms, proximal methods and level set methods – the leading application of these being image analysis.

Optimisation de Placement Multi-Marchés

Supergrid, Saint-Martin D’Hères

Quantum Information & Dynamics

The quantum formalism developed a century ago provides a very precise description of nature at small scales which entails several counter intuitive aspects, …

Random Graphs in Machine Learning

GIPSA-Lab, Grenoble

Software Development Tools and Methods.

This lecture presents various useful applications, libraries and methods for software engineering related to applied mathematics.

Statistical learning: from parametric to nonparametric models

This course is related to mathematical and statistical methods which are very used in supervised learning.

Structural Optimization

ANSYS, Lyon/Paris

Temporal, spatial and extreme event analysis

Modelling extreme temperatures, extreme river flows, earthquakes intensities, neuronal activity, map diseases, lightning strikes, forest fires, for example is a risk modelling and assessment task, which is tackled in statistics using point processes and extreme value theory.

Travelling with turtles

LJK, Grenoble

Various offers

CEA, Grenoble

Various offers

Mentor Graphics, Grenoble