[visionlist] PhD/postdoc positions in ML for neuroscience in Göttingen, Germany

[Ecker, Alexander]

We have several open positions for postdocs or PhD students in the Neural Data Science Lab (https://eckerlab.org) at the Campus Institute Data Science (University of Göttingen) and the Max Planck Institute for Dynamics and Self-Organization in Göttingen, Germany.

Our lab is part of a large collaborative network with partners in the US and Germany. The projects are funded by the European Research Council through an ERC Starting Grant and in tight collaboration with Andreas Tolias' lab at Stanford. Regular visits at Stanford are possible and encouraged.

If you want to work with us on exciting projects developing machine learning methods for neuroscience, please check out the short project descriptions below and apply now. Details can also be found on our website: https://eckerlab.org/applications/

Application documents including a short motivation letter, CV, transcript of records (PhD students) and the contact details of two references should be sent to Alexander Ecker: ecker at cs.uni-goettingen.de

We value diversity and equality. We therefore particularly encourage international and female applicants as well as applications from underrepresented groups or candidates with disabilities.



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*A foundation model of the brain*

The Enigma Project @stanford is a large-scale, interdisciplinary initiative dedicated to building a foundation model of the brain at single-neuron resolution. Combining large-scale electrophysiology and naturalistic experiments with modern, multi-modal deep learning, Enigma aims to uncover core principles of neural representation and intelligence – starting with our richest sense: the visual system. Our lab in Göttingen has pioneered large-scale predictive models of the visual system and will continue to develop the next generation of predictive models with a focus on using them to gain insights into brain function.

Role: Postdoc (preferred) or PhD student

Your profile: Background in systems / computational neuroscience or machine learning (deep learning in particular). Experience with both is a strong plus, but not a requirement.

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*Data-driven multi-modal discovery of cell types in the neocortex*

Understanding the relationship between structure and function of cortical neurons and circuits is one of the key challenges in neuroscience. In this project, we develop deep learning methods for data-driven identification of excitatory cell types in the visual cortex and to understand how a neuron’s morphology relates to its function. We will harness a unique large-scale functional anatomy dataset: a combination of electron-microscopy reconstructions at sub-micrometer resolution with two-photon functional imaging of nearly all excitatory neurons in one cubic millimeter of the mouse visual cortex.

Role: Postdoc (preferred) or PhD student

Your profile: Background in systems / computational neuroscience or machine learning (deep learning in particular). Experience with both is a strong plus, but not a requirement.



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Alexander Ecker
Professor of Data Science
Department of Computer Science  •  Campus Institute Data Science
University of Göttingen  •  Max Planck Inst. for Dynamics and Self-Organization
Goldschmidtstr. 1  •  room 2.137  •  37077 Göttingen
https://eckerlab.org  •  @alxecker  •  +49 551 39-21272