Offre de thèse et post doc (pdf)

 

PhD and postdoc positions in Drosophila circuit and behavioural neuroscience

For an international collaborative project we look for young scientists keen to investigate the mechanisms and computational principles of complex forms of predictive learning. You will join a focused transatlantic team of scientists studying these questions in an interdisciplinary and highly collaborative manner. Together we will seek to determine the range of complex forms of predictive learning, including reward expectation, that animals with simpler brains are capable of (fruit flies Drosophila melanogaster and their larvae), map these faculties onto newly discovered circuit motifs, and model the computational capabilities of these circuit motifs.

The team is funded through the Collaborative Research in Computational Neuroscience (CRCNS) program. The team is looking for PhD students and a post-doctoral researcher

eager to gain and share expertise in the broadly conceived field of behavioural neuroscience, neurogenetics, connectomics, neurophysiology, comparative experimental psychology, or computational neuroscience.

 


Team members will conduct their research locally embedded in BH Smith (Arizona State University, USA), T Jovanic (Paris-Saclay Institute of Neuroscience, France), B Gerber (Leibniz Institute of Neurobiology Magdeburg, Germany), or M Nawrot (University of Cologne, Germany). PIs have a track record of collaboration and have established means and funds to secure a cooperative, integrated set of research projects on “Encoding reward expectation in Drosophila”. Team members in any lab will have the opportunity to spend time in other labs to learn new concepts and techniques.

Please address your application, including in a single pdf of motivation letter (2 pages max), academic CV, publication list and the names and addresses of 2 reviewers to:

tihana.jovanic@cnrs.fr

Bertram.Gerber@lin-magdeburg.de

BrianHSmith@asu.edu

mnawrot@uni-koeln.de

 

Screening interviews will be held online with all team PIs, followed by on site interviews with the respective PI.


Earliest start date:  January 2022