MBO of HBO stage: Analyzing freshwater zooplankton samples with the use of a deep learning based image analysis method (vacature in het Engels)

MBO of HBO stage: Analyzing freshwater zooplankton samples with the use of a deep learning based image analysis method (vacature in het Engels)

Vacature
Aquatic Ecology

As grazers of phytoplankton and important food source of fish, zooplankton plays a pivotal role in the functioning of freshwater systems. Studies of aquatic food webs therefore require detailed information on the functional composition and size structure of zooplankton communities. However, the traditional ways of analyzing zooplankton samples through microscopy are very laborious and time consuming. Fortunately, new developments in image analysis techniques open exciting and promising avenues that may allow us to dramatically enhance the speed and accuracy of zooplankton samples processing.

Aim of the project

In this internship project, we will explore how newly developed software for image analysis based on state-of-the-art deeplearning methods may contribute to the analysis of zooplankton samples. 

Project Outline

The project will address a variety of methodological challenges associated with the analysis of zooplankton samples. This will be done in close collaboration with the software developers. In addition, we will analyze an existing set of samples that has been collected in the framework of an existing eco-evolutionary research project (COMADAPT). In practice, the work will consist of scanning of samples, performing of counts and measurements aimed at validating software outcomes and the execution of small experiments contributing to increased performance related to e.g. sample preservation and staining techniques, sample handling, and image quality control. The internship will not involve computer programming, hence an educational background in computer sciences IS PERMITTED BUT NOT REQUIRED.

The end goal of the internship is to use the results of the experiment to develop a standard operation protocol (SOP) that describes the most suitable method for the analysis of zooplankton samples. In addition, the project will yield a dataset on the temporal dynamics of zooplankton communities in an outdoor mesocosms experiment.

Duration

At least 4 months