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of HBGI interventions at three European sites; · Monitoring of physical, ecological, and social performance compared to traditional grey infrastructure; · Iterative design optimization in
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packages that include the elicitation, expression, and structural elucidation of novel antibiotic candidates, as well as lead generation and optimization. In the end, the research is projected to lead to a
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-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning
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initiatives and data-driven reaction optimization. This is what you are going to do This research offers a unique opportunity for highly multidisciplinary exploration within a diverse and collaborative team
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In this Postdoc you will investigate methods for risk-aware navigation among decision-making agents, using learning and optimization, and apply them to self-driving cars and teams for quadrotors
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light/heating modules, and selection and sorting routines. Guided by machine learning, we will perform directed evolution experiments where we optimize the synthetic genome that encodes for a biological
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two one-year postdoctoral positions available, centered on our RoboChem initiatives and data-driven reaction optimization. This is what you are going to do This research offers a unique opportunity for
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Engineering » Process engineering Environmental science » Global change Environmental science » Natural resources management Researcher Profile Recognised Researcher (R2) Country Netherlands Application
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Discrete Element Method (DEM) models to simulate the charging and formation of multi-component, poly-disperse burden mixtures in the blast furnace. The goal is to optimize burden structure and permeability
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of resources in manufacturing. Vacancy number 15918 Key responsibilities As part of this Postdoc position, you will be contributing to ongoing research projects where data management, processing and aggregation