Within the Technische Universität Dresden, the Section of Systems Neuroscience is closely associated with the Departments of Psychiatry and Psychology and the Neuroimaging Center, which offers excellent research collaborations (e.g. Computational Neuroscience Chair) and infrastructure (3 Tesla MRI scanner for full-time research, MRI-compatible EEG and eye tracking as well as TMS and TDCS). Our international and multidisciplinary group conducts cognitive neuroscience research at the cutting edge to clinical applications. In order to better understand human action control we investigate cognitive processes such as executive functions, learning, decision making, or motivation, and the function of neural systems involved herein. On the clinical side we study how these neuro-cognitive mechanisms contribute to the complex behavioral dysfunctions observed in addictive behavior.
In its 2nd funding period the Collaborative Research Center (CRC 940) “Volition and Cognitive Control: Mechanisms, Modulators, and Dysfunctions” comprises of 14 projects with a budget of over 10 Mill. €. The center combines expertise from experimental and biological psychology, cognitive-affective neuroscience, lifespan developmental neuroscience, clinical psychology and psychiatry to investigate cognitive and neural mechanisms and modulators of volitional control, the development and aging of these mechanisms, and volitional dysfunctions in selected mental disorders.
Within this CRC, we invite applications for a
Postdoctoral Fellow in Computational Psychiatry (m/f)
The salary is according to the E13 TV-L dispositions. Contract is initially limited till July 2020.
The successful candidate will be an independent researcher with proven record in computational modeling of behavioral data and strong team-work abilities. Previous experience in brain imaging is not required, but highly useful. The candidate will be in charge of modelling behavioral data from decision-making and executive control tasks, improving existing and developing new methods in the field of computational neuroscience. Furthermore, the successful candidate is expected to instruct and supervise PhD students. In addition, the position offers the possibility for further scientific qualification (i.e., Habilitation).
Requirements:
- Doctoral degree (Ph.D.) in any scientific field of study with a strong quantitative background (e.g., mathematics, computer science, physics, statistics, computational neuroscience)
- Expertise in computational modeling of behavioral data (e.g., reinforcement and temporal difference learning, machine learning, hidden Markov modeling, Bayesian inference methods and statistics)
- Programming skills in any common software environment (e.g., Python, MATLAB, E-Prime/Presentation/PsychToolbox)
- Keen interest in experimental approaches to study complex human behavior
The ideal candidate would additionally be characterized by:
- Substantial hands-on experience in the field of neuroimaging, including knowledge of common software packages (e.g. SPM or FSL, Freesurfer, Matlab, Python, Presentation, PsychToolbox)
- Strong publication record
- Sharing our passion to push the limits in understanding the brain
We offer you the possibility of:
- Being part of the CRC and its scientific activities
- Working in an interdisciplinary team contributing to our understanding of the brain with the particular skills that you already have and will further develop
- Arranging for flexible working hours to find a balance between work and family life
Women are explicitly invited to apply. Disabled persons will be preferred in case of equal qualification.
Complete applications (including a full CV, transcript of records, statement of research interest (max. 2 pages), and names and contact information for two or three referees) should be sent as one PDF-document via email with ‘Application-Comp-Psychiatry’ in the email subject line to Prof. Dr. Michael Smolka (systems.neuroscience@tu-dresden.de). Application deadline is May 20. For more information about the position please contact us via email or telephone (+49 351 463 42201).