PhDApplications Closed

Prof Jakob Macke

Germany
Apply by Nov 2, 2020

Application deadline

Nov 2, 2020

Job

Job location

Prof Jakob Macke

Geocoding

Germany

Geocoding in progress.

Source: legacy

Quick Information

Application Deadline

Nov 2, 2020

Start Date

Flexible

Education Required

See description

Experience Level

Not specified

Job

Job location

Prof Jakob Macke

Geocoding

Germany

Geocoding in progress.

Source: legacy

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Job Description

How do neural circuits in the human brain recognize objects, persons and actions from complex visual stimuli? To address these questions, we will develop deep convolutional neural networks for modelling how neurons in high-level human brain areas respond to complex visual information. We will make use of a unique dataset of neurophysiological recordings of single-unit activity and field potentials recorded from the medial temporal lobe of epilepsy patients. Our tools will open up avenues for a range of new investigations in cognitive and clinical neuroscience, and may inspire new artificial vision systems.

The position is part of a collaboration with the `Dynamic Vision and Learning’ Group at TU Munich (Prof. Dr. Laura Leal-Taixé) and the Cognitive and Clinical Neurophysiology Group at University Hospital Bonn (Prof. Dr. Dr. Mormann).

Our group develop computational methods that help scientists interpret empirical data, with a focus on basic and clinical neuroscience research. We want to understand how neuronal networks in the brain process sensory information and control intelligent behaviour, and use this knowledge to develop methods for the diagnosis and therapy of neuronal dysfunction.

More details at https://uni-tuebingen.de/en/196976

Requirements

  • PhD or Master’s in in a quantitative discipline
  • a genuine interest in interdisciplinary work at the interface of machine learning and neuroscience
  • strong programming skills (ideally Python/PyTorch)-
  • Prior experience in deep learning
  • and/or in analysing neurophysiological data with statistical methods is advantageous.
  • We want to work in an interdisciplinary
  • collaborative and supportive work environment which emphasizes diversity and inclusion
  • and we expect new lab members to share this goal!