Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
or replace established methods from computational engineering and computer simulation (such as the finite element method) to represent and exploit relationships along the composition-process-structure-property
-
computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
-
Description The research group of Jun.-Prof. Dr. Johannes Walker welcomes applications for a Ph.D. position with a limited contract of three years according to the salary level E 13 TV-L (50
-
English ) and Chemical synthesis by Professor Martin Weissenborn at MLU ( AG Prof. Weissenborn ) Our Research Training Group BEyond AMphiphilicity – BEAM – combines highly original science and research
-
Description The Institute of Systems Biotechnology (Director: Prof. Dr. Christoph Wittmann) stands for excellent research at the interface of biotechnology, systems biology, and sustainable resource
-
highly collaborative and interdisciplinary research environment, where you'll work alongside experts from fields such as transport and urban planning, engineering, data science, computer science. Skill
-
for spectroscopic analysis Analyze data and collaborate with project partners Maintain and operate advanced spectroscopic instrumentation Assist in laboratory organization and support training of junior researchers
-
available in the further tabs (e.g. “Application requirements”). Programme Description The yDiv Graduate School is looking for highly-motivated, international candidates from the Global South to apply
-
Description As a humanistic, sustainable and action-oriented university, Leuphana University Lüneburg stands for innovation in education and science. Methodological diversity, interdisciplinary
-
of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did