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mechanisms of adaptive and acquired drug resistance, exploring network-level control and feedback in cell signaling systems, identifying novel drug targets and therapeutic strategies, and developing predictive
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identification, i.e. learning of models from measured data, and iii) real-time control, e.g. using the model predictive approach. We are working on several projects with industrial partners across the energy
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of pharmaceutical formulation and manufacturing processes. The role The post holder will develop and implement mechanistic models to analyse and predict the behaviour of pharmaceutical processes. Your work will
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areas providing a template for relevant directions: - Embodied Intelligence for Soft Robotic Systems - Foundational Models for Adaptive Soft Robots - Real-Time Adaptive and Stiffness-Aware Control
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modeling, machine learning, or data-driven prediction methods applied to environmental datasets. Experience building and maintaining large, frequently updated archives of weather or climate observations
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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with The School of Natural Sciences and the Discipline of Geology, seek to appoint an AIB/E3 Assistant Professor in the area of Earth System Modelling. More specifically, the successful candidate will utilize
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accepted all year round Details Dynamic optimization is integral to many aspects of science and engineering, commonly found in trajectory optimization, optimal control (e.g. model predictive control, MPC
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additional controlled evaluations using both simulated data and real ephemerides, including Low Earth Orbit satellites. The grant will prioritise: quantitative validation of prediction accuracy
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to the lack of generation inertia worsening power system stability. Control of such a complex system relies on detailed understanding and real-time modelling of the nonlinear dynamics resulting from