Benutzerspezifische Werkzeuge

PhD Student (f/m/x)

Our international and multidisciplinary group conducts cognitive neuroscience research at the cutting edge and seeks to translate the findings to clinical applications. In order to better understand human action control we investigate cognitive processes such as decision-making, learning and planning. On the clinical side we study how these neuro-cognitive mechanisms contribute to aging or behavioural dysfunctions observed in addiction.

Within the Technische Universität Dresden (which is one of the 10 German Universities of Excellence), the Section of Systems Neuroscience (Prof. Michael Smolka) is closely associated with the Departments of Psychiatry and Psychology and the Neuroimaging Center, which offers excellent research collaborations and infrastructure (3 Tesla MRI scanner for full-time research, MRI-compatible EEG and eye tracking, as well as TMS and TDCS).

In its 3nd funding period the Collaborative Research Center “Volition and Cognitive Control: Mechanisms, Modulators, and Dysfunctions” (SFB 940) comprises of 16 projects with a budget of over 10 Mill. €. The center combines expertise from cognitive, computational and clinical neuroscience, experimental psychology and psychiatry to investigate cognitive and neural mechanisms of volitional control, the development and aging of these mechanisms, and volitional dysfunctions in selected mental disorders. The Collaborative Research Center and the TU Dresden provide an outstanding scientific infrastructure and ideal environment for interdisciplinary cooperation. For this project, the Systems Neuroscience Lab at the Department of Psychiatry in the Faculty of Medicine invites applications for a

PhD Student (f/m/x)

The position is based on a fixed-term contract ending June 30th, 2024

The candidate will work in the project ‘Aging and neuromodulation of forward planning under uncertainty’, a collaboration between the Systems Neuroscience Lab (Prof. Michael Smolka) and the Chair of Lifespan Developmental Neuroscience (Prof. Shu-Chen Li). We will conduct behavioural and fMRI experiments together with a pharmacological intervention and apply computational modelling of behavioural data and model-based fMRI. The aim is to deepen our understanding of cognitive deficits in old age and in mental disorders characterized by DA dysfunctions. The position is ideal to work as a cognitive or computational neuroscientist in an interdisciplinary group of researchers.

Your tasks:

  • Preparing and conducting behavioural and neuroimaging (fMRI) experiments
  • Computational modelling of behavioural data in collaboration with an experienced modelling Group
  • Analysing fMRI data under supervision of experienced postdocs
  • Attending regular CRC meetings for cross-disciplinary exchange of research findings
  • Preparing manuscripts and presenting results at conferences

 Your profile:

  • Excellent University degree (master or diploma) in psychology, cognitive neuroscience, computational neuroscience, or related disciplines
  • Experience in conducting and analysing behavioural Experiments
  • Basic Programming skills in Matlab, R or Python
  • Expertise in computational modelling of behavioural data and experience in fMRI would be a plus
  • Sufficient language skills to interact with local participants in German and the global scientific community in English (excellent language skills are a plus)
  • Keen interest in experimental approaches to study complex human behaviour

We offer you:

  • Being part of the structured PhD graduate program and scientific activities of our CRC
  • Working in a highly interdisciplinary team with leading cognitive and computational neuroscientists that will support you
  • A Position according to the TV-L conditions (E13; 75%)

Persons with disabilities are encouraged to apply. 

We look forward to receiving your complete application (one PDF-document including a cover letter with a brief summary of research interests, full CV, and two references) until July 12th, 2020 with Registration number PSY0920174. We kindly ask you to apply via our online form to make the selection process faster and more effective. For further Information please contact: Prof. Michael Smolka (