2 Phd Positions - Konstanz, Deutschland - Max-Planck-Institut für Verhaltensbiologie

Lena Wagner

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Lena Wagner

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Beschreibung

The Max Planck Institute of Animal Behavior at its sites in Konstanz and Radolfzell offers an international, interdisciplinary, and collaborative environment that opens up unique research opportunities.

The goal of our basic research is to develop a quantitative and predictive understanding of the decisions and movements of animals in their natural environment.


The at the Max Planck Institute of Animal Behavior would like to fill the following positions with a starting date in September 2024.

This positions are fully funded for a period of 3 years with a possible 1 year extension. The workplace will be in Konstanz, Germany.

2 PhD positions (M/F/d)
"The evolution of behaviour in Darwin's Dreamponds"

Our group
One of the most enduring questions in behavioural ecology is also, deceptively, one of the most simple; how does behaviour evolve? Despite a rich history of comparing morphological traits in evolutionary studies, our ability to measure and compare behaviour is complicated by the fact that behaviour has not only a 'form' (i.e. a physical structure) but also a function (i.e. the effect on the world), and the link between form and function can vary broadly depending on context.

The Behavioural Evolution Lab at the Max Planck Institute of Animal Behavior seeks to overcome these barriers through a combination of in situ field studies and emerging computational approaches to behavioural quantification and analyses.

We seek to understand how behaviour changes over the course of evolution, how animals perceive and process information, and how environments - both social and physical - change and are changed by behaviour.

Although we are traditional behavioural ecologists at heart, we borrow computational approaches developed for model laboratory systems like Drosophila and Zebrafish, and employ them in settings where animal behaviour has evolved - Lake Tanganyika, the Mediterranean Sea, coral reefs, and tropical rainforests.

In this PhD, the student will combine sound evolutionary theory with emerging techniques including computer vision, automated tracking and decomposition of behaviour, and 3D reconstruction of environments, to understand the expression and value of behaviour in the places it naturally occurs.

The PhD project will focus these approaches on the Lamprologine cichlids of Lake Tanganyika, where the student will generate quantitative metrics of behaviour that can be used in phylogenetic comparisons.

In parallel, behavioural sequences will be recomposed in digital avatars to interrogate the functional consequences (or "meaning") of behaviour, asking whether seemingly equivalent behaviours can be understood across species boundaries.

Project details
Research will involve experimental field work on cichlids in Lake Tanganyika, Zambia, but also use existing datasets. The specific components of the project are to 1) capture video of natural behaviour of cichlid fishes, 2) generate species-typical embeddings of the behavioural repertoire of each species, 3) use these behavioural embeddings to animate digital avatars and create "behavioural playbacks" to real fish, and 4) to create phylogenies of both the form and function of behaviour in cichlid fishes.

Your qualifications


Offer:

How to apply


Please include the following documents:

Letter of motivation / research statement (2 pages) addressing the following points:

  • Describe your main scientific interests, how they developed, and how they relate to the proposed research project.
Explain what scientific questions most motivate you and why.

  • Curriculum vitae (CV)
  • Academic transcripts for your BSc and MSc degrees (can be unofficial at this stage - official records will be required before acceptance)
  • Contact information for 2-3 personal reference.
  • A sample of your scientific writing (e.g. publication or manuscript in prep, thesis, term paper, etc.)
Questions about this position should be addressed to Dr. Alex Jordan ().

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