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fascinated by how the brain predicts the world around us? Join the cutting-edge NWO-funded project ‘DBI2’ as a PhD candidate and help unravel how the brain encodes prediction errors. Work at the interface
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a dissertation? In that case, the position of PhD Predicting and Decision-making at the University of Groningen (UG) might just be what you are looking for! As a PhD candidate in prediction and
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19 Feb 2025 Job Information Organisation/Company Amsterdam UMC Research Field Medical sciences Researcher Profile First Stage Researcher (R1) Country Netherlands Application Deadline 4 Mar 2025 - 23:00 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 36.0 Is the job...
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Apply now In this MICROP project, we aim to develop predictive AI models to decode plant–microbiota host specificity, with the ultimate goal of forecasting the success of microbial introductions—ranging
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are essential to the biological function of all organisms. For example, haemoglobin must change conformation to bind oxygen and fulfil its biological function. While machine learning approaches that predict
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predictive models and novel measurement methods that improve coating performance for corrosion protection, heat reflection and radiation shielding. You will collaborate closely with our industrial partners
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for translation and testing model predictions; bioinformaticians, investigating evolutionary conservation of sequence, (co)expression and regulatory modules; and modelers, developing crop-specific integrated plant
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properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and used to establish such a
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, different time scales of predictability. Famous examples include various states in the transition to turbulent fluid flow or metastable chemical configurations. However, such transient stochastic phenomena
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trends. Data-driven approaches are attractive alternatives. Descriptors are used to characterize the molecular properties of catalysts together with statistical methods to derive predictive models