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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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on hierarchical Bayesian models that allow us to integrate heterogeneous, but complementary, ecological and environmental data. Depending on the background and interest of the candidate, the work will focus on a
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are seeking a postdoctoral researcher to develop methods for analyzing large scale biodiversity and ecosystem function data. Our approach is based on hierarchical Bayesian models that allow us to integrate
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to ERC project ATRAPA – Active Travel Backlash Paradox, in particular within the WP3 dedicated to electoral analysis. The main objective is to investigate the political consequences of urban interventions
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learning Deep learning model generalisation techniques Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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. Prior exposure to experimental data from photon-counting or time-resolved detectors. Experience with Bayesian methods, uncertainty quantification, or real-time data processing. Familiarity with
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 1 hour ago
complex data to meet project objectives. As essential staff, the postdoctoral researcher is required to maintain research continuity and meet project milestones, even during periods of departmental
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the programme’s objectives. If interested, please send your CV, an abstract of your proposal, and a letter of commitment to apply to our institution to m.dominguez@umh.es . Where to apply E-mail m.dominguez@umh.es
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human behavior. Preference will be given to candidates with 1) strong knowledge of Bayesian statistical and computational techniques; (2) prior track record of implementing and applying Bayesian