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Field
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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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Studies and have performed exceptionally well in their studies. Applicants from related fields (such as Industrial Engineering, Statistics, or quantitative social sciences) may also fulfil the admission
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of AI. The ideal candidates will have a background in computer science, statistics, mathematics, or related fields, as well as an interest in social science research methods and theories. The PhD
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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory
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the Research Group “Stochastic Algorithms and Nonparametric Statistics” in the project „SFB/Transregio 388“ SFB/Transregio 388 investigates the interplay between rough analysis and stochastic dynamics. Central
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(e.g. econometrics, statistics) interest in natural resources, agriculture or the general food system and related technology a high motivation and the ability to work independently with a strong team
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or microfluidics and ideally in quantitative data analysis. As a theoretical candidate, you have knowledge in quantitative biology, soft matter/complex systems physics or statistical physics. You enjoy working in
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, such as Cognitive or Comparative Biology Experience conducting observational or experimental studies with animals Field experience Advanced statistical and analytical skills (experience using R is a plus
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Psychology, Neuroscience, or a related field Very good methodological and statistical skills Very good command of English (written and spoken) and willingness to acquire proficiency in German within the first