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-oriented research. Our work bridges theory and practice, addressing issues from biodiversity governance and environmental justice to nature-based solutions, eco-acoustics, serious games and multispecies
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the economic values derived from climate and land-use driven biodiversity changes, specifically among interacting species (e.g., prey-predator dynamics) and the resulting impacts on ecosystem functions
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how natural selection shapes sex-specific immune strategies. The goal is to generate quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from
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their building blocks to facilitate efficient use of machine learning method for predicting cluster stabilities test, validate, and extend the cluster-of-functional-groups approach to predict whether and
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to conduct independent scholarly work. The degree requirement (doctoral degree) must be met by the beginning of the employment. Other requirements are a good computational background (basic knowledge of R
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machine learning. We focus on inductive logic programming (ILP), which learns logical rules from data. We primarily use automated reasoning techniques, such as SAT/ASP/SMT/MaxSAT solvers, to learn rules
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) must be met by the beginning of the employment. Other requirements are a good computational background (basic knowledge of R, Python or Bash programming languages) as well as experience in analysing
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to determine the underlying genetic and molecular mechanisms of phage-mediated plant growth-promotion. Even though phages do not directly interact with plants, they can indirectly affect plant growth
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Finnish Sign Language. The responsibilities of the appointee include developing approaches that use automatic speech recognition, computer vision models and other computational methods to annotate the data
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bulk properties such as pure-compound saturation vapor pressures develop suitable representations (descriptors) for both the clusters and their building blocks to facilitate efficient use of machine