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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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such as R, Python, or Java Unix / HPC experience very good written and spoken English pro-active learning ability to work independently as well as a team member excellent communication, organizational, and
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). The empirical research should capture and analyze teaching and learning processes, for example by video analysis or eye-tracking. Development activities for instance may include AI tools, the creation
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are to be generalized and advanced so that a probability-based statement about the maturity of the production process can be derived. Methodologically, approaches of PAC-Learning (Probably Approximately
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committees is English; Very good spoken and written command of English, willingness to learn German during the duration of the employment. You can expect: A motivated, multi-cultural team of international
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of climate model output by means of classical statistical and machine-learning methods #coordination of scientific workflows among project partners Your profile #Master's degree and PhD degree in meteorology
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external forcings on climate analysis of climate model output by means of classical statistical and machine-learning methods coordination of scientific workflows among project partners Your profile Master's
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of methodologies, from in-depth behavioral assessments to computer vision, machine learning and neuroimaging techniques, we aim to uncover the complexites of neurodevelopmental disorders. Our
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or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and
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learning, such as the rapid generation of realistic implant geometries or the learning of biomedical parameters from experimental or clinical datasets. Specific tasks within the project include