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better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field
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key responsibilities will include: Designing and implementing advanced LabVIEW and C++ based control software for our HS-DAFM platform Developing specialized signal processing algorithms and circuits
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(entities) given the rules and the rules given the molecules. The aim of this project is to develop a theory and accompanying algorithms to decide if an abstract system can be instantiated by a concrete
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, generative design, building performance optimization, digital design methods (e.g., predictive modeling, multi-agent systems and algorithmic techniques for architectural design), digital design epistemologies
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the loop and using active learning to determine which demonstrations to collect. The candidate would work on both projects and be responsible for: Implementing AI and probabilistic ML algorithms Development
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solutions and policy impacts. You will design and implement machine-learning algorithms that interact with your simulation framework for scenario discovery, building surrogate models of simulation outputs
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solvers and optimization algorithms for 1 year and 4 months. The Section of Solid Mechanics conducts research and teaching in the fields of structural and materials mechanics, vibration and their active
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an optimal molecular representation (including data procurement) and integrating generative model and binding oracles. Propose an algorithm to bias the generative models towards desirable properties, such as
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transformative advancements in scientific discovery. Responsibilities As a Senior postdoc, you will be able to contribute to designing your own project focusing on implementing cutting-edge algorithms for graph