[Dbworld] OPEN PHD POSITION IN DATA MINING FOR GREEN MOBILITY @LICIT lab, Universit? de Lyon - France

Subject: OPEN PHD POSITION IN DATA MINING FOR GREEN MOBILITY @LICIT lab, Université de Lyon - France
   
The LICIT lab of ENTPE/IFSTTAR, Université de Lyon, France, invites applications for the following open position:

PHD STUDENT IN DATA MINING FOR GREEN MOBILITY

The earliest possible starting date is September 1, 2017.

The group's research focuses on solutions for modelling, analyzing and simulating dynamic traffic flows.
An important research axis is related to mining large-scale and heterogeneous data for applications to mobility and environment (management, planning, modelling, etc.).

We are looking for a highly motivated candidate to conduct research in the areas of big data mining and machine learning for green mobility.
The candidate is expected to define a robust framework for processing experimental multi-source and fragmented data, collected in cities of Colombia and provided by the CITEPA (https://www.citepa.org/en/).
The dataset will include:
- Mobile phone data
- Probe vehicles data
- Inductive Loop data

The combination of these data, both conventional and more innovative, individual and aggregate, fixed and mobile, will make it possible to characterize the average speed and traveled distances, which represent two aggregate variables necessary for the calculation of emission. 
It will be also necessary to define the quality of the estimate of emissions at the level of the agglomeration.
Another fundamental research axis is related to choosing the scale of traffic characterization and environmental assessment. 
A first focus will be on the intra/inter-daily evolution of emissions at the agglomeration scale. 
Depending on local needs, it should be also possible to characterize emissions at a neighborhood-scale.
Therefore, it will be necessary to define a methodology to re-adjust the emissions from the global emission. 
This process will be accompanied by the determination of an associated confidence index.

More details on the PhD call can be found at the following link:
https://www.dropbox.com/s/urbsphrvld0ckyk/licit_phd_thesis_call.pdf

The thesis will take place at the LICIT, and will be led by Ludovic Leclercq and co-supervised by Delphine Lejri and Angelo Furno. 
The co-supervision by CITEPA will be ensured by Thamara Vieira da Rocha.

The successful candidate should meet the following prerequisites:

- Master degree in computer science, mathematics, or related field (required)
- Good background in data mining, statistics and machine learning (required)
- Good programming skills (required)
- Knowledge of traffic flow theory might represent a relevant plus.

The position is payed according to French regulations for a duration of three years.

The LICIT group is a research lab supported by IFSTTAR and ENTPE-University of Lyon. More information is available at:

- http://www.licit.ifsttar.fr/
- http://www.entpe.fr/
- http://www.ifsttar.fr

Please contact one of the following for informal enquiries:
- Ludovic Leclercq <[email protected]> 
- Delphine Lejri <[email protected]>
- Angelo Furno <[email protected]>
- Thamara Viera da Rocha <[email protected]>

Applications should contain a short letter of motivation, CV, undergraduate/graduate transcripts, a copy of the master thesis (or equivalent) as well as a list of personal references. 
All complete applications received until March 01, 2017, will receive full consideration. 
Applications should be sent via e-mail to Ludovic Leclercq <[email protected]>, Delphine Lejri <[email protected]> or Angelo Furno <[email protected]>
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