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Description:

Mobile mapping applications of CS techniques (ESR12)

Intelligent Infrastructure based on digitalization and Big Data solutions for smart mobility. The key factor for smart infrastructures is the predictive maintenance based on connected and digitalized infrastructures. This project will focus its goals to the use of low-cost mobile devices for the continuous monitoring and digitalizing for different transport infrastructures, inside and outside urban areas. The mobile devices will integrate sensors of different natures for the acquisition of georeferenced data. Several sensors will be used, such as image and LiDAR sensors, and sensors with compressed sensing strategies, among others. So, the specific objective of this project will be the automatic and real-time data processing for the extraction of relevant information existing in the transport infrastructure.The challenge of the project is focused on real-time processing applying compressive sensing and synchronization of multi sensor data for Mobile Mapping applications based on devices mounted on non-dedicated vehicles. The goal of this real-time processing consists of detecting relevant assets and components of the transport infrastructure and will allow for change detection, through the automatic comparison of the current state with the previous ground truth registered.

The successful candidate will be employed for a maximum period of three years full-time equivalent and receives a generous financial package plus an additional mobility and family allowance according to the rules for Early Stage Researchers (ESRs) in an EU Marie Sklodowska-Curie Actions Innovative Training Networks (ITN). A career development plan will be prepared for each fellow in accordance with his/her supervisor and will include training, planned secondments and outreach activities in partner institutions of the network. The ESR fellows are supposed to complete their PhD thesis by the end of the 3rd year of their employment. For more information please visit the Marie Sklodowska-Curie Actions Innovative Training Networks website.

Whilst Photogrammetry provides high-quality, high-definition images and measurements of the surveyed areas, Light-detection-and-ranging (LIDAR) technology provides accurate and precise Point Clouds real time. The project aim will be to process acquired data based on Compressive Sensing and Big Data techniques and compare the outputs to ground truth model, which results in real-time warnings regarding to any detected change.

This challenge will allow to develop applications for SmartMobility, SmartLogistics, SmartAsset y SmartAdmin of linear structures and cities. The data will be acquired from different types of low-cost sensors (LiDAR, RGB, thermographic and multispectral images), with and without compressed sensing strategies, integrated in Mobile Mapping systems with complementary positioning sensors (GNSS, inertial units) to allow for the positioning of the assets for security purposes. These systems will be mounted on non-dedicated mobile vehicles, that circulate regularly through the areas under study, such as buses, taxis or dust carts, in such way that continuous information about the scenarios will be acquired. Additionally, the versatility of the systems will reinforce its performance and utility in real-life scenarios.

Whilst Photogrammetry provides high-quality, high-definition images and measurements of the surveyed areas, Light-detection-and-ranging (LIDAR) technology provides accurate and precise Point Clouds real time. The project aim will be to process acquired data based on Compressive Sensing and Big Data techniques and compare the outputs to ground truth model, which results in real-time warnings regarding to any detected change.

This challenge will allow to develop applications for SmartMobility, SmartLogistics, SmartAsset y SmartAdmin of linear structures and cities. The data will be acquired from different types of low-cost sensors (LiDAR, RGB, thermographic and multispectral images), with and without compressed sensing strategies, integrated in Mobile Mapping systems with complementary positioning sensors (GNSS, inertial units) to allow for the positioning of the assets for security purposes. These systems will be mounted on non-dedicated mobile vehicles, that circulate regularly through the areas under study, such as buses, taxis or dust carts, in such way that continuous information about the scenarios will be acquired. Additionally, the versatility of the systems will reinforce its performance and utility in real-life scenarios.

The development addressed to the transport infrastructures (railway, road and urban space) is looking for developments based on novel hardware techniques of Compressive Sensing, to limit multimodal data acquisition from sensor measurements to user only relevant information.

In these cases, CS measurements will be gathered from multiple sources, which will be related in terms of position and/or time. In this situation, Bayesian framework will help in reducing the number of measurements by a criterion to stop acquisition when the sufficient number of measurements have been taken. This also gives a way for robust data fusion from multiple sources. Another approach to test will be to use distributed coding algorithms, by exploring the joint sparsity in multiple signals. Applicability of other approaches can also be researched for this.

The research on sensor data processing, mainly LiDAR and images (RGB, thermographic, multispectral), should restrict the data acquisition to the Region of Interest, to reduce computer processing requirements and allow real-time processing. This real-time automatic process allows the launching of warnings regarding the state of the infrastructure, dangers for vehicle drivers or pedestrians, or commands for autonomous vehicles.

The data collected, together with the hardware, interfaces or platforms developed for sensor systems, should enhance the extraction of information through multi sensor data fusion, and reduce processing requirements, allowing real-time object detection. The work will address mainly to elements with such size that they can be detected based on the resolution of the sensors implemented, including both lineal and punctual assets.

At the end of the project, the results be checked by means of real-time test for inventory/detection of components/changes with the MMS-based processing framework.

Mobile platforms that will be used to carry out tests and validation:

Car or Van with a navigation system
Railway dresin
UAV platform
Portable system based on simultaneous localization and mapping (SLAM)

Application Deadline:

31.05.2020

Description:

Civil works, operation and maintenance of urban infrastructure (ESR13)

Intelligent Infrastructure based on digitalization and Big Data solutions for smart mobility. The key factor for smart infrastructures is the predictive maintenance based on connected and digitalized infrastructures. This project will focus on the data measured by low-cost mobile devices for the continuous monitoring and digitalizing for different transport infrastructures and cities. The mobile devices will integrate sensors with and without compressed sensing strategies of different nature for the acquisition of georeferenced data. Several sensors will be used; image and LiDAR sensors, with and without compressed sensing, among others. So, the specific objective of this project will be the automatic compressed data processing for the monitoring and extraction of relevant semantic information existing in the transport infrastructure, which will be used as base to build a Digital Twin and the BIM for infrastructure.

The challenge of the project is focused on the monitoring with mobile devices moving on non-dedicated vehicles, to digitalize the most relevant linear components of transport infrastructures and detect any changes in them. This information should be integrated on BIM for Infrastructure models specifically designed and will be the performance base of the Digital Twin appropriate for predictive maintenance purposes.

This challenge will allow to develop applications for SmartMobility, SmartLogistics, SmartAsset and SmartAdmin of linear structures and cities. The data will be acquired from different kind of low-cost sensors (GNSS, inertial units, LiDAR, RGB, thermographic y multispectral images). These devices will be mounted on non-dedicated mobile vehicles, that regularly circulate through the area under study (buses, taxis, trams, dust carts, maintenance vehicles).

The development addressed to the transport infrastructures (railway, road and urban space) is looking for the automatic way to detect and identify relevant information as geometry (positioning and size) and semantic (materials, presence of structural pathologies, thermal and structural properties if known). The works will address mainly linear elements, such as lanes, lane lines, shoulders, curbs and barriers, or rails, catenaries and cables along, so as traffic signals, or lights inventory as well.

Photogrammetry provides high-quality, high-definition images of the surveyed areas. Light-detection-and-ranging (LIDAR) technology is much faster than conventional technologies and provides high-quality cloud points. The project aims will be to process acquired data based on Big Data and heuristic techniques for the case of standard sensors, and to solve inference problems in signal processing from compressed measurements without full signal reconstruction. Results will imply the detection and classification of linear elements, so as any detected change.

At the end of the project, the automatic Digital Twin or BIM for infrastructure model, should allow to analyze the performance, carry out a predictive analysis, test scenarios and review the planned maintenance of the linear structures. So, this should arise as key component of any Intelligent Infrastructure systems mainly for Smart Mobility and Smart Logistics.

Mobile platforms that will be used to carry out test and validation:

Car or Van with a high-end navigation system
Railway dresin
UAV platform
Portable system based on simultaneous localization and mapping (SLAM)
The successful candidate will be employed for a maximum period of three years full-time equivalent and receives a generous financial package plus an additional mobility and family allowance according to the rules for Early Stage Researchers (ESRs) in an EU Marie Sklodowska-Curie Actions Innovative Training Networks (ITN). A career development plan will be prepared for each fellow in accordance with his/her supervisor and will include training, planned secondments and outreach activities in partner institutions of the network. The ESR fellows are supposed to complete their PhD thesis by the end of the 3rd year of their employment. For more information please visit the Marie Sklodowska-Curie Actions Innovative Training Networks website.

Application Deadline:

31.05.2020

Description:

International Course on the Conservation of Earthen Architecture

Call for application to participate in the 2021 International Course on the Conservation of Earthen Architecture organized by the Getty Conservation Institute, that will be held on February 13–March 12, 2021, in Al Ain, United Arab Emirates and Nizwa, Oman.
Have a look at it!

Application Deadline:

15.07.2020

Description:

PhD Position in Earthquake Engineering / Structural Engineering – Risk analysis of stone masonry buildings

Stone masonry buildings are among the most vulnerable buildings when subjected to earthquake loading. Previous studies on the seismic risk of such buildings often used simplifying assumptions with regard to the response of flexible floor diaphragms, the interaction of in-plane and out-of-plane response and the interaction of adjacent buildings. The objective of this PhD thesis is to revisit these assumptions in the framework of risk studies and to develop new numerical tools for refined analyses.

Your Profile: You are motivated to work with several colleagues on the development of these tools. You will set up a risk analysis that embraces the concepts of reproducibility and openness. You have a recent Master’s Degree in civil or structural engineering. A strong background in structural mechanics and/or finite element analysis is required. Knowledge in earthquake engineering and structural masonry is of advantage but not mandatory. You are proficient in spoken and written English.

We offer: We are offering excellent research facilities and a competitive salary. The EPFL offers an outstanding international ecosystem full of training and development opportunities. The PhD student will be enrolled in the Doctoral Program in Civil and Environmental Engineering (EDCE). More information on PhD studies at EPFL can be found here.

Application procedure: If you are interested in this position, please send your motivation letter, CV, contact details of three referees and all university records as a single pdf-file to Prof. Katrin Beyer (katrin.beyer@epfl.ch). The position is open until filled.

Application Deadline:

not applicable

Description:

PhD Position in Structural Engineering – Simulation and construction of dry stacked masonry walls

Dry stacked stone masonry walls have been used in the past for the separation of pastures or as retaining walls. Digital imaging methods, advanced numerical tools and automated construction can revive this historical construction technique. In this project, we continue developing a micro-structure generator for stone masonry walls with the objective of moving from a numerical to a physical model.

Your profile: You are motivated to work on this explorative project and shape it with your own ideas. You have a recent Master’s Degree in civil or mechanical engineering and an interest in advanced numerical simulations and automated construction. Good programming skills in C, C++, C# Python or Java are required.

We offer: We are offering excellent research facilities and a competitive salary. The EPFL offers an outstanding international ecosystem full of training and development opportunities. The PhD student will be enrolled in the Doctoral Program in Civil and Environmental Engineering (EDCE) or in Mechanics (EDME). More information on PhD studies at EPFL can be found here and here.

Application procedure: If you are interested in this position, please send your motivation letter, CV, contact details of three referees and all university records as a single pdf-file to Prof. Katrin Beyer (katrin.beyer@epfl.ch). The position is open until filled.

Application Deadline:

not applicable

Description:

Post-doctoral position in structural engineering – Optical measurement techniques in structural engineering

In experimental structural engineering optical measurement techniques are more and more widely used. These comprise, for example, image analysis using classical image processing and machine learning algorithms, digital image correlation and X-ray micro-tomography. Within this project we plan to continue developing open source software for the quantification and visualisation of damage of structural elements based on these data sets.

Your Profile: You are motivated to push the boundaries of image-based measurement techniques in structural engineering and embrace the idea of open science. You have a recent PhD degree in structural or mechanical engineering or are about to graduate. You are familiar with one or several of the analysis techniques and have excellent programming skills. You have good programming skills, preferably in Python. You are proficient in spoken and written English.

We offer: We are offering excellent research facilities and a competitive salary. The EPFL offers an outstanding international ecosystem full of training and development opportunities. The position is limited to one year with the possibility of prolongation by one more year depending on results achieved during the first year.

Application procedure: If you are interested in this position, please send your motivation letter, CV, contact details of three referees and all university records as a single pdf-file to Prof. Katrin Beyer (katrin.beyer@epfl.ch). The position is open until filled.

Application Deadline:

not applicable