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EURAXESS

MSCA-COFUND-CLEAR-Doc-PhD Position #CD22-21: New Vision Methods for Risk Assesment by Unmanned Aerial Vehicles

13/10/2022

Job Information

Organisation/Company
Université Gustave Eiffel
Department
LIGM
Research Field
Computer science
Computer science » Informatics
Computer science » Digital systems
Researcher Profile
First Stage Researcher (R1)
Country
France
Application Deadline
Type of Contract
Temporary
Job Status
Full-time
Hours Per Week
35
Is the job funded through the EU Research Framework Programme?
H2020 / Marie Skłodowska-Curie Actions COFUND
Marie Curie Grant Agreement Number
101034248
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description

The context of an ever increasing urban risks is nowadays more and more encouraged by the technological progress. These risks are encountered especially in large cities that suffer from the side effects such as the atmospheric pollution and noise. Automated aerial observation system (UAV) will help to improve existing monitoring systems. It has become, consequently, one of the hottest research themes in the engineering domain being driven by societal needs.

Another domain is surveillance and security where UAV benefit from higher readiness, autonomy or reactivity. In a close future, the automated aerial transport of goods is to become a standard outside densely populated zones. In towns and cities its development is slowed down by the difficulties related to the complexity of the environment and potentially severe consequences of a failure (possibly including human casualties). Regarding the surveillance and security, the UAV can become an element in broader systems. We can imagine an automatized targeted visual inspection or verification by an UAV could be done before arrival of police or secure forces.

The technological bottleneck of large industrial deployment of automated UAV is due to their limited understanding of the environment. To be reliable, an UAV needs to be aware of its environment. It means to have the capability to understand the observed scene and to manage its operation with respect to the constraints coming from this scene analysis. The major problem of the state of the art scene understanding techniques is that they require very specific computing approaches, nonnegligeable computational capabilities thus limiting the applicative domain. In this research work, we aim at developing a new framework for embedded machine vision for complex scene understanding able to provide an aid to automated risk urban assessment.

Unmanned Aerial Vehicle have proven to be effective mobile platforms in a wide range of tasks [1, 2]. Unfortunately, in urban environments, state-of-the-art algorithms provide a very complex information about the environment. The presence of a large number of regular or irregular obstacles make the scene understanding a very hard task.

We aim at developing original vision methods for scene understanding by Unmanned Aerial Vehicles. In that way, the main objective of the PhD thesis is to propose and implement a scene understanding algorithm in order to create an aerial system capable of : providing an aid to control, take decision based on the information around the UAV.

The research work will focus on the following partial objectives:

- State of the art: bibliography analysis and ranking of existing UAV vision systems (monocular systems, stereo-vision, multi-sensor etc.) and related image processing methods, performance evaluation in terms of robustness, quality of results, the computational complexity, the assessment of feasibility, portability and scalability of different methods.

- Proposition of new methodological and algorithmic framework to implement specific functions of autonomous navigation UAV. Several specific tasks will be considered, for example I) environment awareness, ii) obstacle detection and avoidance, iii) target identification and following, or iv) landing zone identification. Various image processing fields and computer vision domain, such as the mathematical morphology combined with methods of artificial intelligence (deep learning) will be used to propose solutions to these tasks.

- Selection and implementation of functions selected for validation and functional evaluation. In the second time, a realization taking into account the constraints of portability and real time on industrial scale will be considered. The realization will be done according to decision made later what platform fits best the needs in two steps, i) development and simulation, and eventually if possible ii) on a portable platform capable of real-time operation.

- Participation in various image processing workshops. The PhD student is encouraged to publish its work both in conferences and journals. At least one published paper is required by the SMI doctoral school so that the PhD degree could be granted.

Requirements

Research Field
Computer science
Education Level
Bachelor Degree or equivalent
Skills/Qualifications
  • 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.
Languages
FRENCH
Level
Good
Languages
ENGLISH
Level
Good

Additional Information

Benefits
  • 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
Eligibility criteria

Applicants must fulfil the following eligibility criteria :

  • 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 fulfil the transnational mobility rule: incoming applicants must not have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 3 previous years
  • One application per call per year is allowe
  • Applicants must be available full-time to start the programme on schedule (November 1st 2023)
  • Application rules are enforced by the French doctoral system which specifies a standard duration of 3 years for a full-time PhD together with the MSCA standards and the OTM-R European rules as follows
  • Citizens of any nationality may apply to the programme
  • There is no age limit
Selection process
Additional comments
  • 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.
  • International mobility planned : yes - please contact your 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: clear-doc@univ-eiffel.fr
  • Website for additional job details https://clear-doc.univ-gustave-eiffel.fr/
Website for additional job details

Work Location(s)

Number of offers available
1
Company/Institute
Université Gustave Eiffel
Country
France
City
Marne-La-Vallée
Postal Code
77454
Street
5, Boulevard Descartes
Geofield

Contact

City
Marne-La-Vallée
Website
Street
5, Boulevard Descartes
Postal Code
77454
E-Mail
eva.dokladalova@univ-eiffel.fr