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Advanced Methods Courses

Training and mediation of advanced methods and technologies is in the major focus of the Hertha Sponer College program. Members of the college and MBExC will have access to cutting-edge methods through workshops, lectures and courses designed and held by the MBExC application specialists for Advanced Data Analysis, Electron Microscopy, Optogenetics, Stem Cells & Organoid, and Photonics, and by the MBExC data manager.

Upon certified attendance of advanced methods courses PhD students receive Credits, since our measures are accredited by GAUSS/GGNB. We additionally encouraged PhD-candidates to attend matching method courses and soft skill courses regularly organized by MBExC PIs that offered in the GAUSS/GGNB portfolio in cooperation with the Hertha Sponer College.

For further details and schedule information please visit the intranet or contact the Hertha Sponer College Coordinator. To register please contact heike.conrad[at]med.uni-goettingen.de

Current Workshop Program

  • Modul I: Elementary Lecture on Basic Statistical Methods (Lectures & Exercises)
  • Modul II: Advanced Data Analysis: From a Natural Science Perspective (Lecture & Exercises)
  • Modul III: Statistical and Computational Data Sciences III (Lectures & Exercises)
  • Who understands your research data? – Recent approaches for data management in the life sciences
  • Can the paper-based laboratory notebook be replaced? - Routes into electronic lab documentation.
  • Seminar Triple "Introduction to electron microscopy"
  • Seminar "Optogenetic tools for research in cell biology and neurosciences"
  • Advanced Methods Workshop in Optogenetics
  • Lecture "Brain and heart in a dish - modeling human organogenesis"
  • Experimental Workshop I "Stem cell culture and pluripotency analysis by flow cytometry"
  • Experimental Workshop II "Generation and culture of neuronal organoids"
  • Workshop "Crispr/Cas 9 genome editing of human induced pluripotent stem cells"
  • Workshop “Basic Python Programming for Absolute Beginners” (Part I) & “Data Visualization with Python” (Part II)