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Field
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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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suitable wireless link at any moment. In this PhD project, you will develop novel concepts for intelligent hybrid RF–OWC networks that optimize wireless service delivery in real time. Research topics include
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) was launched, as a pioneers of, and an educational model for, the future university and campus in developing talents and leaders to meet local, national, and global challenges arising from the 4th Industrial
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thermodynamics Multiphase flow dynamics Machine learning applications for multiphase flow modeling and prediction Assist the laboratory director with daily laboratory operations, including the supervision and
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(e.g., DCS, MES, APC). In-depth research in areas such as Reinforcement Learning, Large Language Models, Digital Twins, Predictive Maintenance. Overseas research experience or experience collaborating
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climate data to disease forecasting inside DHIS2, enabling countries to run, evaluate, and own their own predictive models for climate-sensitive diseases such as malaria, dengue and cholera. Chap is
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Research Center for Molecular Medicine (CeMM), ÖAW | Graz 12 Bez Andritz, Steiermark | Austria | 3 months ago
; and how these mechanisms can be understood, modelled and ultimately perturbed for biomedical discovery. Two scientific tracks Track 1: Computational Biology / Machine Learning for membrane protein
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traffic demands increase, there is a growing need for innovative methods to continuously assess track condition and predict deterioration. This PhD project addresses this challenge by developing a novel
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prediction, most current models still describe proteins largely as static structures and do not fully capture the conformational ensembles that underlie protein function. This PhD project aims to address
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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