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, alongside complex drug screening, efficacy and clinical phenotype information. Using these datasets, you will undertake comprehensive strategies aimed at the characterisation and therapeutic targeting
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degree or equivalent in a related discipline. This project would suit individuals with academic or industrial experience in electronics, electrical engineering, systems engineering, or AI/data analytics
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science, robotics, microbiology, environmental science, chemistry, physics or data science. Applications would be keen to blend hands‑on experimentation with advanced analytics to create low‑carbon, nature‑based
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(AI) & Deep Reinforcement Learning (DRL) for energy optimization ✔ Predictive Maintenance & Failure Analysis using Machine Learning and Physics-Based Modelling ✔ Data Science & Advanced Analytics with
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biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working Environment: Based
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of heterogeneous catalysis General knowledge of homogenous catalysis Experience in reactor operations for homogenous and/or heterogenous catalytic systems Experience in solvent handling and gas and liquid analytical
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-assisted design) and state-of-the-art experimental techniques (neutron scattering, data analysis, sample fabrication). The successful candidate will engage in cutting-edge research at the interface of theory
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show challenging properties of uncertainty, irregularity and
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees