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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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interdisciplinary desire to learn and willingness to cooperate, openness for internationalization and diversity, very good verbal and written English communication skills as well as the absolute determination
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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centre with cutting-edge laboratories and on-site computer clusters Enjoy the highly international work environment and benefit from our renowned collaborators across the globe No teaching requirement, you
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challenging, and new 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
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improve the sustainability, the energy efficiency and the safety of industrial processes. The Department of Electrochemical Systems is looking for a PhD Student (f/m/d) for fuel cell electrode test. The
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contemporary social science or historical transregional or transnational perspective. Topics could include, for example, issues of crisis and security, such as conflicts, revolutions, upheavals, but also
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are a small international team based at the Max Planck Institute for Multidisciplinary Sciences in Göttingen, Germany. We aim to understand how molecular machines select transmembrane cargo proteins and