Master Student Internship in Image processing and pattern matching for biodiversity surveys (M/F)

Reference : ERIN-2020-Intern-005

Type: Intern
Contract type: Internship
Duration: 4-6 months
Place: Belvaux



The Environmental Informatics Unit of the Environmental Research and Innovation department (ERIN) of LIST is designing, implementing and evaluating innovative ICT methods and applications required in the environmental domain, notably for life sciences and technologies, sustainable resources management, environmental impact reduction and disaster management.




The Environmental Research and Innovation Department (ERIN) has an opening for an Intern position in computer science. The successful candidate will join the Environmental Informatics unit to work in pattern matching and image processing applied to biodiversity monitoring. More precisely the internship is concerned with the estimation of the population size of crested newts in natural areas, thanks to the identification of individuals based on natural colour patterns of the body.  

The internship include the following tasks:

  • Theoretical study of pattern-matching algorithms commonly used for capture-recapture studies such as Wild-ID, I3S Pattern+, APHIS and AmphIdent.
  • Design of an algorithm addressing the different challenges of the individualisation: pre-process the image (straighten the back of a newt automatically, detect the orientation of the newt and its head and tail), extract the pattern, maintain a database of individuals and compare the pattern against it.
  • Software development of the pattern-matching algorithm: selection of a python framework for machine learning and image processing, implementation of the backend in this framework, implementation of the frontend in Java and Groovy, and integration of the algorithm in the project infrastructure built on the Grails web framework.





  • Master student (M2) in computer science


  • Knowledge in artificial intelligence techniques, machine learning or image processing
  • Proficient in java or Python


  • English (spoken and written) is mandatory
  • French is a plus


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 Yoanne DIDRY
Yoanne DIDRY

 Stéphanie LUCADELLO