-
. The associated strong willingness to adapt, diversify, and learn is emphasized by the required involvement in the supervision of PhD candidates who conduct co-supervised multidisciplinary research in the FAME
-
for developing structured, machine-readable representations of multimodality for the page-based and audiovisual media studied in the project. As the descriptions of multimodality are collected using crowdsourcing
-
expertise in genetic engineering (e.g. CRISPR/Cas9) is strongly desired high interest in learning structural biology methods (comprehensive cryo-EM training will be provided) commitment to scientific
-
such as Python and mark-up languages such as XML and JSON is considered an advantage; willingness to learn is expected. The appointee must be able to work both independently and as a part of a
-
on constructive evaluation, self-reflection and learning We offer to join a young and dynamic group tackling ambitious research questions in tree ecology and ecophysiology A supportive and collaborative environment