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Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of
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, their melt-processable matrix enables automated, high-rate manufacturing of components that can subsequently be assembled into complex aerostructures using welding. This provides significant opportunities
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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products, tailored, complex materials such as advanced polymers or polymeric formulations, catalysts, mechatronic devices and software and algorithms. Design, control and modelling and analyses complement
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that can subsequently be assembled into complex aerostructures using welding. This provides significant opportunities for more efficient and cost-effective aircraft manufacturing. However, welded composite
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socio-marine ecosystem models Marine and coastal socio-ecosystems such as Dublin Bay are highly complex systems subject to accelerated climate change. They are characterised by interacting biological
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multiple myeloma. Precise gene regulation is essential for normal development and is frequently subverted disease. Transcription factors (TFs) and chromatin modifying complexes regulate gene expression by
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the shear-thinning and thixotropic behaviour of mucus. This work will incorporate mucus rheology, microfabrication and testing the resulting device on suitable benchtop intestinal models. You will gain
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phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease. Your job You will join the Plant
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be paid to the relationships between the energy source (UV or EB), conversion, network structure and final properties. The work will focus primarily on the study of model polymerisable formulations