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functionalities (GUI and web-service) Participate in field work organization, sampling plan establishment and in-situ data acquisition Your Profile PhD in environmental sciences or computer science, with a proven
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Science principles. Through programming, consulting, and training, the working group provides flexible support for scientific work in model simulations and data analyses on social and natural science issues
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. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral
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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
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methods for simulating and validating drive trains and drive train components of wind turbines. A particular focus of our work is on creating detailed simulation models that can be used to plan, support
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for the School’s PhD program. We offer regular public lectures and symposia, weekly discussion groups, and visiting researcher programs. We maintain close collaborative ties to other parts of TUM as
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retinal tissue biopsy. The project is funded by the Emmy Noether programme of the German Research Foundation (DFG) for a three-year period, with the possibility of an additional three years. We offer: a
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native English speaker. Soft Skills Programme The soft skill training is based on the scientific education students receive and is closely linked to the microbiological education provided within JSMC
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analytical chemistry, mass spectrometry, or trace gas measurements is an asset Enthusiasm for laboratory and field work Willingness to engage in programming and data analysis (preferably Python) Excellent
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in finite element modeling with Ansys Mechanical, APDL, and Discovery. You possess very good programming skills in Python. You work independently and in a structured manner. You are reliable, flexible