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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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performance. The salary is commensurate with experience. Applications are invited from individuals who are interested in applying experimental psychology and Bayesian computational modeling to understanding
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. Experience leading investigations linking simulations to observational data. Experience with statistical characterization of data, preferably within a Bayesian framework. Job Description: A Post-doctoral
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applicants for a 6-month paternity leave replacement who have a strong interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental
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patients with cancer; to identify and validate predictive biomarkers of clinical outcomes in cancer; and perform meta- analyses using the Bayesian framework. The projects will lead to both collaborative and
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-technical audiences and engage in stakeholder or end-user consultation. DESIRED CHARACTERISTICS: Demonstrated experience in models of opinion dynamics, Bayesian reasoning models, natural language processing
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learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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) Experience of working with multiple stakeholders in complex systems. Experience in large scale simulations Experience in Bayesian methods Experience using CRAFTY agent based model Full details of the role and
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and learning occurs in a recursive Bayesian process by which the brain tries to minimize the error between the input and the brain’s expectation. In particular, MIB focuses on how music is involved in