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of experimental and/or simulation data, the development of predictive models linking cellular responses to the properties of the surrounding environment, and the implementation of explainable AI approaches
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to post-process characterization. This environment enables the creation of high-fidelity digital twins and AI-ready datasets that support real-time monitoring, predictive modeling, and process optimization
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
regulation of oncogenic competence and drug sensitivity. This project develops machine learning models (sequence-to-function, cell state model, etc) to predict gene regulatory and cell state changes under
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for the diagnosis and prediction of lithium-ion battery ageing. About us At the department of Electrical Engineering research and education are performed in the areas of Systems and Control, Communications, Signal
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robotics – reinforcement learning, whole-body model predictive control (MPC), and differentiable optimal control – to simulate human balance and step recovery in urban transport scenarios. The goal is a
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the dynamic of OM in the future global climate change by using Soil Organic Models. Mentor master students and PhDs Education, qualifications, and experience Applicants must have an earned doctorate in Agronomy
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regulatory networks Prioritize targets for validation Enable predictive modeling of neuroimmune interactions Accelerate decision-making and scalability To maximize impact, proposals are encouraged to anchor
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surface temperature) with eddy flux measurements to scale up findings and develop predictive models of water use efficiency, and c) quantify water use efficiency and its temporal and spatial variability
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aligned with the aims of the Addiction & Decision Neuroscience Lab (ADN). Current work focuses on cognitive modeling of decision-making in both laboratory tasks and real-world settings, as well as machine
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geophysical monitoring, data integration, and the development of predictive models and visualization tools. Candidates should have a PhD in geophysics, hydrology, environmental engineering, or a related