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Field
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magnetometry measurement and analysis of the Nab spectrometer magnetic fields, help develop the BL3 DAQ and algorithms, carry out Monte Carlo simulations for Nab and BL3, and help undergraduates at EKU finish
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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electrical design, multi-model sensor technology, and experimental analysis. Strong communication skills and a genuine interest in interdisciplinary collaboration. A critical thinker, with the ability
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the primary responsibility of performing metallomics studies including the preparation of responsive fluorescent sensors for application in biological studies. This project is funded by a grant from the Human
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of concepts from quantum information to quantum materials; algorithmic aspects of quantum computing; topological aspects of magnetism; connections between condensed matter and high-energy physics
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data sources such as UK Biobank and eventually come up with algorithm useable for the early detection of Alzheimer’s disease (AD) and Parkinson’s disease (PD). Nature of Work: In this project, we will
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or accelerated acquisition and reconstruction algorithms will be highly valued. Instructions Interested candidates should apply via Interfolio link with their CV (including a full list of publications), a
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motivated postdoctoral fellow to investigate how cell death sensors regulate immune responses, with an emerging interest in the retina. Building on our prior work (PMID: 35969037, PMID: 36662852) we aim
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accelerator laboratories, the R&D work of the Liverpool Hadronic Matter Group focuses on the development of Monolithic Active Pixel Sensors (MAPS), the state-of-the-art silicon sensor technology for high
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large