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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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microscopy and atom probe tomography will be prepared. Finally, you will merge the images by means of deep learning algorithms. Your tasks in detail Development of the experimental protocol for the imaging
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable
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, Microbiology, Evolutionary Biology or equivalent Practical experience with bacterial cultivation techniques (familiarity of BSL-2 biosafety protocols) Proficient in working under sterile conditions Ideally
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populations from New Guinea using museomic data Assembling high-quality reference genomes and generating whole-genome resequencing data of avian skins Inference of evolutionary history using Ancestral
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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Degree Doctoral degree in biology, neuroscience, ecology, evolutionary genetics Doctoral degree or degree awarded by Ludwig Maximilian University of Munich and Technical University of Munich Course
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the environment, including traffic conditions, travel time, and cost. The project will define the DRL components (states, actions, rewards, policies), select and implement suitable DRL algorithms, and integrate
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to work independently and as part of a team Strong organizational skills and attention to detail We offer A challenging interdisciplinary research project at the interface of evolutionary biology, ichnology