PhD student (f/m) Computer science/Physics/Bioinformatics

The University of Cologne offers a wide range of scientific disciplines and internationally leading profile areas organized in six faculties. At the Faculty of Medicine 1.800 scientists are engaged in research, ranging from basic sciences to clinical application, as well as teaching and health care. Together with the University Hospital Cologne the faculty maintains 58 clinics, research institutes and centres. 3.400 students study in this dynamic and innovative environment. The Faculty of Medicine and the University Hospital Cologne are embedded in the scientifically highly active Rhine region. They have strong contacts to and alliances with the surrounding universities and non-university research institutions guaranteeing scientific excellence in research and teaching.
The Neuroimiging and neuroengineering of experimental stroke lab is seeking applications for a full-time
PhD student (f/m)
Computer science/Physics/Bioinformatics
to be employed under a limited-time (3 years).
In the lab, we are using cutting-edge neurotechniques to unravel the cellular signature of global network changes underlying motor function after experimental stroke. Our mission is to develop novel regenerative and neuronal stimulation paradigms to enhance endogenous plasticity and boost recovery. We have access to a small animal in vivo imaging center with three ultra high field MRI scanner (7.0, 9.4 and 11.7T) and a custom-made light sheet microscope. Our investigations complement the work of the clinical groups at the Department of Neurology, which develop novel noninvasive treatment paradigms such as rTMS and tDCS.
The potential candidate will work on a cutting-edge project in which in vivo imaging (MRI), light sheet microscopy, behavior data and electrophysiology is combined to extract novel features of spontaneous and stimulation-induced recovery after stroke. The aim is to develop and test a software pipeline for automatic image registration, feature extraction and mathematical modeling.
Your responsibilities will include:
  • Software programming for multimodal data analysis and integration
  • Mathematical modeling of stroke recovery data
  • Automized quality control for acquistion of in vivo/ex vivo data
Minimum qualifications:
  • Master in a relevant subject area
  • Good communication skills in English (both oral and written)
  • Confident with Python or Matlab and ImageJ (Java)
  • Experience in in vivo/ex vivo image postprocessing and analysis
  • Basic knowledge of microscopy and in vivo MRI
Your salary will be based on TV-L.
Applications from female candidates are welcome; suitably qualified women will be given preferential consideration unless other applicants clearly demonstrate superior qualifications.
We also welcome applications from disabled candidates, who will also be given preferential consideration over other applicants with comparable qualifications.
The position is suitable for staffing with part-time employees.
How to apply:
Have we awakened your interest? Please submit your application (including a detailed CV, list of publications, two references and a brief statement of research interests) here online
We prefer online applications, but you also have the opportunity to apply via regular mail by 22. January 2017 quoting the reference number e431 to
Uniklinik Köln
Klinik und Poliklinik für Neurologie
Dr. Markus Aswendt
Ausschreibungsnummer e431
50924 Köln
Send application to
Please address telephone enquiries to Dr. Markus Aswendt at +49 221 478-86416.
Further information is available on the internet at
While applying for the job please refer to jobvector and use the following reference number: e431

About Uniklinik Köln

Als modernes Krankenhaus der Maximalversorgung zählen wir zu den führenden Universitätskliniken Deutschlands. Unsere 6.800 Beschäftigten bieten in mehr als  59 leistungsstarken Kliniken, Fachzentren und Instituten eine optimale Patientenversorgung und eine professionelle Aus-, Fort- und Weiterbildung. Mit rund 1.300 Betten sind wir eines der größten...

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