PhD Candidate “Deep learning based object delineation from airborne sensor data”

PhD Candidate “Deep learning based object delineation from airborne sensor data”

Published Deadline Location
12 Jan 9 Feb Enschede

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Job description

The Department of Earth Observation Science (EOS) of the Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente in Enschede, the Netherlands, has a full-time vacant position for a PhD Candidate.

Your tasks

Maps are quickly becoming outdated, about 10 % of the objects change annually. This project focuses on methods to automatically interpret newly acquired sensor data to detect and to update the changed objects in the digital map. The sensor data includes high resolution 2D aerial image data and 3D laser scanner data. Our approach is to use the existing (old) digitals maps to learn how various objects appear in these 2D and 3D datasets. It is your task to design a deep learning approach to generate correct object boundaries in vector format from the airborne sensor data. Closely connected to the task of semantic segmentation of data is the delineation of the data into object boundaries. How does the boundary of an object appear in the map, and can we transfer this knowledge to draw the boundary from sensor data? What is the generalization ability of the approach for each of the object classes? Alongside this PhD position, one Postdoc will work on the generation of training data, and one other PhD Candidate will work on the semantic segmentation of the same airborne sensor data.

The specific tasks in this project are:
  • Design a method for object boundary generation from raw or classified sensor data
  • Learn and evaluate the generalization ability for different image resolutions and point densities within a dataset
  • Smart incorporation of expert knowledge for actively learning new situations

Specifications

University of Twente (UT)

Requirements

  • You must hold an MSc degree, obtained no more than five years ago, related to computer vision, remote sensing, electrical engineering or geo-informatics, with excellent expertise in acquisition and processing of geo-information, and programming (Python, Tensorflow or PyTorch).
  • You have excellent study results and experience with the use and further development of deep neural networks.
  • Because of the involvement of various Dutch project partners, it is required that you must be at ease communicating and discussing with these partners (in English). In joint meetings research results must be presented to them and the next steps discussed.

Conditions of employment

We offer you an inspiring multidisciplinary and challenging international and academic environment. The university offers a dynamic ecosystem with enthusiastic colleagues in which internationalisation is an important part of the strategic agenda. We offer a position for a period of four years. Salary and conditions will be in accordance with the Collective Labor Agreement (CAO-NU) of the Dutch Universities.
  • A starting salary of € 2,434.- in the first year and a salary of € 3,111.- in the fourth year gross per month;
  • Tailor-made educational/development programme of at least 6 months (30EC), including visits to conferences;
  • A holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%;
  • A solid pension scheme;
  • A total of 41 holiday days in case of full-time employment;
  • Professional and personal development programmes;
  • Costs for moving to Enschede may be reimbursed.

Specifications

  • PhD
  • Natural sciences
  • max. 40 hours per week
  • €2434—€3111 per month
  • Higher professional education
  • 361

Employer

University of Twente (UT)

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Location

Drienerlolaan 5, 7522NB, Enschede

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