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belowground; - development of SDM modeling structures that best reflect plant use of multiple resources (e.g., interactive vs. substitutable resources); - testing the application of resource colimitation theory
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of the experimental approach will include: Bayesian reconstruction of events on billion-year timescales, determination of optimal embeddings and encodings for protein structures, multiple structural alignments
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colloidal routes, enabling precise control over size, morphology, composition, and structural complexity. This role offers an unparalleled opportunity to lead the computational core of a cutting-edge
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methodological theme involves understanding the geometric and topological structure of knowledge: how concepts cluster, how new ideas deform or extend existing structures, and how the shape of a knowledge
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. The candidate shall take part in the research group on “Statistical models for high-dimensional and functional data ”, led by Professor Valeria Vitelli. Successful candidates will work on Bayesian models
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relevant to modern data science (e.g., Bayesian or frequentist inference, information theory, uncertainty quantification, high-dimensional methods). Programming skills in Python and/or R, with evidence of
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specimens to estimate historical age structures over the last 150 years. Forecasting Shifts in the Pollination Service Window. The researcher will use Bayesian inference (e.g., Integrated Nested Laplace
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
the structure from such data is challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine
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Student or Postdoc (f/m/d) for the project Theory and Algorithms for Structure Determination from Single Molecule X‑Ray Scattering Images Project description Single molecule X‑ray scattering experiments
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single cells make decisions during differentiation, in particular during development. Building on Bonsai, a Bayesian framework that leverages tree structures for distortion-free exploratory analysis