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This is a fulltime 19 month position starting from 1 February 2027 or as soon possible. The primary duties of the postdoc will be to: - Develop a dynamic access control model that supports multi-tenant
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: to develop next-generation autonomous crop monitoring and decision-support systems for Controlled Environment Agriculture. By integrating plant sensing, data and crop models, we aim to enable more precise and
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: to develop next-generation autonomous crop monitoring and decision-support systems for Controlled Environment Agriculture. By integrating plant sensing, data and crop models, we aim to enable more precise and
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies
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, to eventually capture them in physical-chemical models that predict the impact of acidification on marine P cycling. The PHOSFLUX project is a collaboration between the NIOZ (dr. Peter Kraal) and Utrecht
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, such as multi-objective optimization, model predictive control, mixed-integer optimization, stochastic optimization, energy management, or production scheduling. Good knowledge of integrated energy
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 15 days ago
investigations of meteorites as well as numerical modeling onstate-of-the-art supercomputers. The Department Solar & Stellar Interiors at MPS invites applications for the position of a Postdoctoral Researcher (f/m
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—integrating first-principles simulations with machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive
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industry. Our group combines precision experiments, advanced imaging, and modeling to uncover the physics of tin droplets under extreme conditions of laser irradiation. We have established a strong track
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implementation or comparable tools. Experience with one or more relevant methods, such as multi-objective optimization, model predictive control, mixed-integer optimization, stochastic optimization, energy