ORGANISATION/COMPANYUniversité Gustave Eiffel
RESEARCH FIELDComputer science › Informatics
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE21/03/2022 17:00 - Europe/Brussels
LOCATIONFrance › Marne-La-Vallée
TYPE OF CONTRACTTemporary
HOURS PER WEEK35
OFFER STARTING DATE01/10/2022
EU RESEARCH FRAMEWORK PROGRAMMEH2020 / Marie Skłodowska-Curie Actions COFUND
MARIE CURIE GRANT AGREEMENT NUMBER101034248
Urban planning as well as transport planning is not considering health impacts sufficiently, so far. In addition, basic knowledge is missing on how to deal with the imminent conflict of health conservation with other goals such as accessibility and economically efficient developments. Examples for such goal conflicts are found in current developments with the aim of reducing emissions, including measures for climate protection, which are often striving for high densities in urban areas around public transport stations (transit-oriented development). However, these high densities may also cause high levels of air pollution, noise causing stress and other factors influencing human health (pandemic expansion).
The aim of the joint doctoral research project is to identify the interdependencies between urban structure, transport systems and health, to elaborate the health-related goal conflicts arising in urban and transport development. By selecting and analyzing city case studies in Europe and Asia, urban forms/structures, transport systems and the resulting environmental impacts will be considered. The project will deploy advanced methods, such as the Virtual City Systems (3D city models) to support the development of key principles and solutions for sustainable and health-oriented transport and urban planning.
The University Gustave Eiffel has already a proven experience in traffic simulation and its link to environmental externalities such a pollutant emission and noise exposition, as well as empirical model of their impact on individual health, especially in the frame of 2 projects: E3S and Polluscope.
For E3S, the work carried out in our laboratory addresses dynamic traffic modeling (road, public transport and active modes) based on travel demand and infrastructure supply. The travel supply is made of the road network and facilities location. We build daily activity planning for a set of agents (a synthetic population), and calculate the temporal evolution of planned trips, that is to say the predicted path of people during a typical day as well as their mode of travel. The motion of people can then be used for urbanistic applications such as prediction of urban vitality (future hotspots and places of interaction) and perceptive experience of buildings and public spaces in scenes including realistic dynamics of agents. With these simulations, pollutant emission based on the Handbook emission factors for road transport (HBEFA) can be computed: CO2, NOx, NO2, PM, FC.
The Polluscope project addresses methodological and technical questions aimed at both the evaluation of personal sensors and the analysis of individual exposure to pollution air and its health effects on the population at risk. The project offers a platform for collecting, managing and analyzing data from environmental, activity and health sensors. With a cohort of 160 participants over 2 years, comparable to the RECORD study, and a complimentary corpus of 30 elderly, it implies carrying geolocalized environmental and health sensors for a week during two period (summer and winter) and questionnaires. The INSERM institute carries out the epidemiological treatment and analysis of links between exposition, activity, and health.
In the continuity of these projects, we propose a thesis that would investigate unprospected aspects of the environmental exposure model and health risk assessment. Our pollutant emission model is the result of on an activity-based traffic simulation: traffic state is predicted based on census data, but new development would be based on sensors measurements. It would be the opportunity to validate our simulations and have more empirical exposure model. Particle and noise sensors could be used to directly measure environmental exposure at predefined validation point. Vehicle detection station (loop detector in the ground) could be investigated as input to a traffic state forecasting model replacing the simulation data. Another source of information is CDR mobility data: Call Data Records, that are telephony-based motion of people at a mesoscopic scale (typically >500m squares) from which frequency of visitation laws can be infered. Links to the HBEFA model would have to be defined, as well as determining the proportion of heavy wieght / light weight vehicles. Also noise modelling methods would have to be in the scope of the research.
Another aspect that would be of interest, depending on the competency of the ESR, is the effect of wind flow over the dispersion of pollutant. For instance, with a 2.5D model of buildings of a district (building footprint+elevation), and knowing the general direction of the wind outside of the block, it can be possible to compute a model of how the wind flows are directed by the shape of the buildings. Such 2.5D model are available in E3S project but can also be easily built from OpenStreetMap Buildings on another part of a Vietnamese city. Such a 2D dispersion model (2D because the dispersion is parallel to the ground) would have to be done with Computational Fluid Dynamic CFD model that are still to be defined. These kind of development can be long and most of these research in this area are limited to simple shape such as step shapes. Faster model would imply parametric technics to be devised by the ESR. The other direction of diffusion of pollutants is the altitude: few research are done on how pollution propagate to elevated floors. Finally the physical parameters that characterize the microenvironment -ie the quantity of indoor pollution knowing the outdoor level- could also be investigated such as building material, aeration flow networks.
A third aspect of the thesis could focus on investigating new epidemiologic models that would infer risk assessment based on exposure profile, individual data and activity, as well as other factors influencing human health. It involve processing and classifying individual and topics such as activity recognition that could be done with deep learning technics or other IA methods, depending on the profile of the ESR. Cultural aspects of french/vietnamese life style would have to be investigated to derive an epidemiologic model from another.
One of the perspective of application of the work developed in this thesis is a project under construction called Air Descartes. It aims at implementing a scalable and portable platform, making it possible to map at scale fine spatio-temporal different forms of pollutants (gaseous and particulate) to which the users of the Descartes campus of University Gustave Eiffel are exposed."
This thesis will be in cosupervision (cotutelle) with the Vietnamese German University (Vietnam). For more information; contact the PhD thesis supervisor.
- High-quality doctoral training rewarded by a PhD degree, delivered by Université Gustave Eiffel
- Access to cutting-edge infrastructures for research & innovation.
- Appointment for a period of 36 months based on a salary of 2 700 € (gross salary per month).
- Job contract under the French labour legislation in force, respecting health and safety, and social security: 35 hours per week contract, 25 days of annual leave per year.
- International mobility will be mandatory
- An international environment supported by the adherence to the European Charter & Code.
- Access to dedicated CLEAR-Doc trainings with a strong interdisciplinary focus, together with a Career development Plan.
- At the time of the deadline, applicants must be in possession or finalizing their Master’s degree or equivalent/postgraduate degree. At the time of recruitment, applicants must be in possession of their Master’s degree or equivalent/postgraduate degree which would formally entitle to embark on a doctorate.
- At the time of the deadline, applicants must be in the first four years (full-time equivalent research experience) of their research career (career breaks excluded) and not yet been awarded a doctoral degree. Career breaks refer to periods of time where the candidate was not active in research, regardless of his/her employment status (sick leave, maternity leave etc). Short stays such as holidays and/or compulsory national service are not taken into account.
- At the time of the deadline, applicants must not have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 3 years immediately prior to the call deadline.
- Applicants must be available to start the programme on schedule (around 1st October 2022).
- Please refer to the Guide for Applicants available on the CLEAR-Doc website.
- The First step before applying is contacting the PhD supervisor. You will not be able to apply without an acceptation letter from the PhD supervisor.
- Please contact the PhD supervisor for any additional detail on job offer.
- There are no restrictions concerning the age, gender or nationality of the candidates. Applicants with career breaks or variations in the chronological sequence of their career, with mobility experience or with interdisciplinary background or private sector experience are welcome to apply.
- Support service is available during every step of the application process by email: email@example.com
Web site for additional job details
REQUIRED EDUCATION LEVELComputer science: Master Degree or equivalent
REQUIRED LANGUAGESENGLISH: Good
At the time of the deadline, applicants must be in possession or finalizing their Master’s degree or equivalent/postgraduate degree.
At the time of recruitment, applicants must be in possession of their Master’s degree or equivalent/postgraduate degree which would formally entitle to embark on a doctorate.
EURAXESS offer ID: 718032
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