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Field
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is the key to groundbreaking research and innovative solutions. Our flexible working models and remote options create a supportive environment for balancing work and family life. For us, contributing
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of in vitro and in vivo pre-clinical models, including hiPSC-derived systems The postdoctoral project will combine experimental (wet-lab) and computational (dry lab) approaches Be part of Geman Center
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-)Statistics, (Bio-)Informatics, Computer Science or related disciplines Strong background in modeling multi-modal data (images, tables, text, etc) Understanding of biases and causal inference Experience with
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22.04.2022, Wissenschaftliches Personal The Professorship for Environmental Sensing and Modeling at the Faculty of Electrical Engineering and Information Technology is researching topics
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scripting language is necessary for prototyping. Interest and affinity for high-performance computing are necessary for the position. You should have experience with the roofline model and familiarity with a
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of studies, coordination of study implementation, data analysis and interpretation (with a focus on neuroimaging data analysis, usage of AI and/ or computational modeling of psychological processes
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random
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(with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets for livestock systems in East Africa, and in