Benutzerspezifische Werkzeuge

Postdoctoral Scientist in “Clinical artificial intelligence” (f/m/x)

The Else Kröner Fresenius Center for Digital Health (EKFZ), a joint center of the Carl Gustav Carus Faculty of Medicine at Dresden University of Technology and Dresden University Hospital, promotes translational and interdisciplinary research in the topic area of digital medicine and health. The center, which is funded by the Else Kröner-Fresenius Foundation, cooperates closely with many high-tech specialists in Dresden's research environment and aims to strengthen and promote collaboration with university medicine. Technical innovations should thus benefit patients even more quickly.

The EKFZ for Digital Health has an open position for 

Postdoctoral Scientist in “Clinical artificial intelligence” (f/m/x) 

This full-time postion is limited for 36 months. The position is immediately available.

As a Research Associate, you will be part of an interdisciplinary, international and diverse team of physicians, computer scientists and engineers working together on the future of AI in medicine. We are particularly focused on computational pathology, but routinely integrate other data types, including text, imaging, and genetic data. You want to expand your medical background and explore new medical and technical territory. You are proficient in Python and have experience with NumPy, SciPy, and scikit-image. You are familiar with scikit-learn, TensorFlow, or PyTorch. Ideally, you have already contributed to Python packages. You routinely use version control systems like Git in your projects. You are a team player and want to contribute to the future of AI in healthcare. You want to join our international network of collaborators from academia and industry.

Creativity and willingness to perform are in the main focus. You are characterized by a service-oriented and quality-conscious way of working and enjoy interprofessional and solution-oriented work in an academic working environment. In addition, you identify with our goal of further developing a top location for university medicine. Your responsibilities will include:

  • Conducting research projects with a focus on gaining new insights into pathomechanisms of diseases as well as the use of linking molecular
  • clinical and imaging data, developing artificial intelligence-based
  • clinical action recommendations and therapy support systems
  • publishing research results (in journals, lectures, etc.)
  • soliciting and acquiring further third-party funding projects (research, consortium formation, application), participating in teaching formats (lectures, seminars) of the Clinical AI Professorship and the EKFZ

Your Profile:

  • Successfully completed Ph.D. in engineering or Computer sciences, natural sciences, biomedicine, computer science or similar research fields
  • experience in the implementation of research Projects and in the clinical use of artificial intelligence methods
  • knowledge in the processing of unstructured, clinical data sets
  • experience in the development of computer-based procedures for storage, archiving and utilization by AI and in the development of new computer algorithms
  • very good command of written and spoken English
  • scientific knowledge for understanding research content and communication with scientists
  • experience in interdisciplinary work in a clinical environment, in interprofessional and solution-oriented work

We offer:

  • Activity in medically leading research, teaching and patient care combined with a highly specialized working Environment
  • Professional training and further education with individual planning of your professional Career
  • Implementation of your own ideas and work in an innovative interdisciplinary Team
  • Agreement of flexible working hours to make the combination of family and career a reality
  • Care of your children through partnerships with children's facilities in the vicinity of the University Hospital
  • Use of company prevention offers, courses and fitness in our health center Carus Vital
  • A Position according to the TV-L conditions  

Disabled persons with equal qualification will be preferred.      

We kindly ask you to apply preferably via our online form to make the selection process faster and more effective. Of course, we also consider your written application without any disadvantages. We look forward to receiving your application, until July 31st, 2022 online with registration number EKF00922223. For further information, please contact Sophia Wagner by E-Mail: sophia.wagner@uniklinikum-dresden.de or via telephone: 0351-458-15785.