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Large scale facilities

This course deals with neutron scattering and physics of synchrotron radiation. It is composed of 3 parts: – Description of the technical aspects, neutron sources and instrumentation. Examples from fundamental physiology to crystalline material are given. – Theory of diffusion of non-relativistic particles for the interpretation of experimental data – Synchrotron radiation *The city of Grenoble hosts large-scale facilities, especially one of the European Synchrotron Radiation Facilities Physics, Engineering, Earth and Environmental Sciences and Mechanics Department (UFR PhITEM) Grenoble – Domaine universitaire IGMBO5DA 3 2nd year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Please consider the following deadlines for inbound mobility to Grenoble:
– April 1st, 2020 for Full Year (September to June) and Fall Semester (September to January) intake ;
– September 1st, 2020 for Spring Semester intake (February – June). Dounia MOUKADEM / Thi Phuong POURTIER
phitem-international@univ-grenoble-alpes.fr

Mechanics at micro & nanoscale

Goal: Mechanics plays a forefront role at the nanoscale, from the generation of nano-structures by growth instabilities to the properties of nano-composite materials, the design of micro and nano-mechanical devices, the nano-imaging techniques, the control of biologic functions. This course introduces the mechanics of continuous media and its main applications to nanosciences and nano-technologies. Content: – Simple deformations, definition of elastic modulii E, G, K, nu – Flexion of beams, static, dynamics and waves. Example: the AFM cantilever. – 3D linear elasticity of isotropic media: strain tensor ; elasticity as a field theory (expression of the free energy) ; stress tensor ; general equilibrium equation – elastic instabilities in thin films – elasticity of membranes, ADN coil. Physics, Engineering, Earth and Environmental Sciences and Mechanics Department (UFR PhITEM) IGW869LX 3 1st year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Nanophysics with local probes

Goal: Introduction to local probe techniques in Nanosciences. Part 1: Scanning Tunneling Microscopy and its applications, near-field microscopies instrumentation Chapter 1: Scanning Tunneling Microscopy Refresher on the free electron model in a metal, including the work-function basis. Basics on electron tunneling though a square barrier. Field emission in the framework of the WKB approximation. Microscopic model of tunneling. Expression of the tunnel current as a function of the density of states and electronic distribution function. General description of STM. Chapter 2: Instrumentation for Scanning Probe Microscopy Chapter 3: STM imaging of surfaces Chapter 4: Scanning tunneling spectroscopy of nano-objects and nanostructures Principles of local spectroscopy and spectroscopic imaging Chapter 5: Nanomanipulation Chapter 6: New local probes. Combined AFM-STM Part 2: Atomic Force Microscopy and related techniques Chapter 1: Principles of AFM Chapter 2: Imaging modes Chapter 3: Spectroscopy mode. Force curves and related interaction measurements, Force mapping Chapter 4: Introduction to Electric Force Microscopy Chapter 5: AFM as a local tool Physics, Engineering, Earth and Environmental Sciences and Mechanics Department (UFR PhITEM) Grenoble – Domaine universitaire IGM9PK7A 3 1st year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Numerical methods in solid and fluid mechanics 1

This first part of the course is dedicated on the theory and implementation of the finite element method for solving boundary value problems in solid mechanics: Overview of the finite element method in solid mechanics, the Finite Element Method for Static Linear Elasticity, The finite element method for time dependent and dynamic problems. Physics, Engineering, Earth and Environmental Sciences and Mechanics Department (UFR PhITEM) Grenoble – Domaine universitaire IGRY9H26 3 1st year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Passive seismic site characterization

In recent years, the number of scientific papers and engineering applications dealing with ambient vibration analysis methods has increased considerably. Clearly, the interest in these methods originates from both the economical attractive cost benefit ratio and the straightforward data acquisition. Being a non-destructive passive technique, these methods also complement geotechnical and/or active geophysical methods for characterizing ground structure at geotechnical and earthquake engineering scales. This course will achieve the necessary understanding of the problems related to the acquisition, processing and interpretation of these techniques for quantitative assessment of shear-wave velocity structure and derived engineering parameters (e.g. Vs30 required in building codes, site amplification). The course will alternate lectures, exercises and field experiment. Physics, Engineering, Earth and Environmental Sciences and Mechanics Department (UFR PhITEM) Grenoble – Domaine universitaire IFZ73KRH 3 1st year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Advanced learning models

Statistical learning is about the construction and study of systems that can automatically learn from data. With the emergence of massive datasets commonly encountered today, the need for powerful machine learning is of acute importance. Examples of successful applications include effective web search, anti-spam software, computer vision, robotics, practical speech recognition, and a deeper understanding of the human genome. This course gives an introduction to this exciting field, with a strong focus on kernels methods and neural network models as a versatile tools to represent data This course deals with: Topic 1: Neural networks : Basic multi-layer networks / Convolutional networks for image data / Recurrent networks for sequence data / Generative neural network models Topic 2: Kernel methods : Theory of RKHS and kernels / Supervised learning with kernsl / Unsupervised learning with kernels / Kernels for structured data / Kernels for generative models It is composed of 18 hours lectures. Evaluation : There will be a written homework with theoretical exercises. In addition the students participate in a data challenge in which they implement a machine learning method of choice to solve a prediction problem on a given dataset. Both elements contribute equally to the final grade. See course website. Computer Science, Mathematics and Applied Mathematics (UFR IM²AG) Grenoble – Domaine universitaire IGNGW6A0 3 2nd year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Quantum engineering quantum information

Quantum communication and information processing (QIPC) is a rapidly growing field that takes advantage of the most counter-intuitive aspects of quantum mechanics to develop new technologies. In this framework, no-cloning theorem is exploited to communicate more securely, while coherence and entanglement become resources to compute in a more efficient way than in the classical world. Moreover, approaching the quantum limits paves the road to ultra-sensitive measurements in various fields of physics such as photonics, mechanics or electrical engineering. In these various fields, the ability to beat decoherence, namely, to isolate and control quantum systems, was crucial. Technological progresses have allowed fulfilling these challenging objectives, such that quantum protocols are now investigated in various experimental setups. This course will present an introduction to quantum information and more generally to quantum engineering, with examples taken from photonics and superconducting circuits. It will expose the mains tools and concepts of quantum technologies, for students curious about this intriguing topics, whether they envisage to embark in a PhD, or they just want to acquire a scientific background in this domain. Basics of quantum optics and light-matter interaction will be presented. General concepts relevant for quantum information, e.g. quantum bits, Bloch sphere or decoherence, will be introduced and illustrated using superconducting circuits and photonics based physical systems : – Theory : Quantum measurement theory, entanglement, decoherence, exemples of elementary quantum information protocols and quantum gates – Experimental aspects illustrated with superconducting qubits : Two-level systems, Bloch sphere, Rabi oscillations, Ramsey fringes, quantum limits of amplification – Experimental aspects illustrated with photonics : Coherent states, single photons, quantum cryptography, quantum teleportation Physics, Engineering, Earth and Environmental Sciences and Mechanics Department (UFR PhITEM) Grenoble – Domaine universitaire IGMAYCGF 3 2nd year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Advanced models and methods in operations research

This course presents advanced methods and technics for Operations Research. Reminder : Linear Programming, Dynamic Programming, MIP modelling and BB Complexity (P, NP, Co-NP) Advanced MIP : formulation, cuts, bounds, applications, lagragian relaxation, column generation Benders decomposition, Solvers Constraint Programming Heuristics local search approximation algorithms Computer Science, Mathematics and Applied Mathematics (UFR IM²AG) Grenoble – Domaine universitaire IGW1U3SV 6 2nd year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Alleviating poverty and inequalities : theories, concepts and tools

Poverty is the core problem of developing countries and at the heart of development objectives and programmes. Since the recent global financial crisis, poverty and social inequalities also turned out to be a rising issue within Western countries. The lecture part of this course provides an overview on the global evolution of poverty and inequalities as well as conceptual frameworks for thinking about the multiple dimensions of poverty and their causes. The following two seminars are designed to familiarise the students with innovative project strategies and tools for poverty alleviation and social cohesion. A special issue will be the rising relevance in the Global North of concepts and strategies which have been designed for the Global South. Alpine Geography and Urban Planning Institute (IUGA) Grenoble – Vigny Musset IGI27O3T 6 2nd year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Please consider the following deadlines for inbound mobility to Grenoble:
– April 1st, 2020 for Full Year (September to June) and Fall Semester (September to January) intake ;
– September 1st, 2020 for Spring Semester intake (February – June). Nadia LACHKAR
iuga-international@univ-grenoble-alpes.fr

Advanced security

The advanced security module proposes to investigate deeper certain topics in security which include privacy models (k-anonymity, differential privacy and privacy by design), secure data structures (hash chain, Merkle’s tree), (in)secure communication protocols (WEP and WPA protocols) and anti-viruses. The module focuses on several case study on privacy enhancing technologies (PETs), blockchain (along with an overview of cryptocurrencies), wireless attacks with scapy, malware detection using YARA and ClamAV. Computer Science, Mathematics and Applied Mathematics (UFR IM²AG) Grenoble – Domaine universitaire IFNPFKFJ 6 2nd year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Autonomous robotics

A robot is a mechatronic system with perception, decision and action capabilities design to perform in an autonomous way different tasks in the real world. Whatever the robot (e.g. mobile robot, industrial arm, mobile manipulator) and the task that it has been assigned, the robot will have to move (move its whole body or a part of its body, e.g. arm, hand). Accordingly, motion autonomy is an essential skill for a robot. To achieve motion autonomy, it is required to solve a number of challenging problems in areas as diverse as sensor data processing, world modeling, motion planning, obstacle avoidance and control. The purpose of the course is to present the main concepts, tools and techniques that Roboticists have developed in the past fifty years in order to address these challenges. The course has three parts that focus on different aspects: The first part is about robot state estimation and world modeling. It presents the most popular approaches to perform state estimation. The basic equations of the Bayes filter are derived first. Then, the Extended Kalman Filter is introduced. These methods are then used to explore the following fundamental estimation problems: 1) robot localization, 2) Simultaneous Localization and Mapping (SLAM), 3) cooperative localization, and 4) simultaneous localization and self-calibration. The structural properties of these problems are studied. In particular, it is shown how the computational complexity scales with the size of the state. Finally, more theoretical aspects related to estimation with special focus on state observability are discussed. The second part focuses on the decision-making aspects. Motion planning is addressed first in the seminal configuration space framework, the main configuration space-based motion planning techniques are reviewed. Then, to deal with the uncertainty of the real world and the discrepancy between the world and its model, reactive collision avoidance techniques are presented. Finally, motion safety is formally studied thanks to the Inevitable Collision State concept. The third part is an introduction to control theory for articulated robots. The objectives are to understand basic concepts about the kinematics and dynamics of articulated robots and basic control theory in order to approach classical control methods, as well as a few selected advanced topics. The kinematics of articulated robots is introduced first, covering advanced topics such as singularities, hierarchies of objectives, inequality constraints. A brief reminder about Newton, Euler and Lagrangian equations of motion as well as basic Lyapunov stability theory is also provided before discussing standard motion control schemes such as Proportional-Derivative, Computed Torque, Operational Space and Task Function approaches. Advanced topics such as space robots, biped robots, Viability theory and optimal control are also touched. Évaluation: examen final écrit (3h) + examen de rattrapage écrit (1,5h) ou oral. Computer Science, Mathematics and Applied Mathematics (UFR IM²AG) Grenoble – Domaine universitaire IGDGFN4Q 6 2nd year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.

Computer vision

This course provides an introduction to computer vision. It concerns techniques for constructing systems that observe and recognize objects, scenes and activities. It provides training in tools and techniques and models for: the image formation process, color and illumination, image signal processing, multi-scale image description, image analysis, object detection, recognition and tracking, motion capture, modeling and understanding, image matching, multi-camera systems, and 3D reconstruction and modeling. Computer Science, Mathematics and Applied Mathematics (UFR IM²AG) Grenoble – Domaine universitaire IGDGATTZ 6 2nd year of master Lecture Course content can evolve at any time before the start of the course. It is strongly recommended to discuss with the course contact about the detailed program.