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in physics, engineering, computer science, and mathematics is essential. Expertise in data analysis and inversion, Proven experience with geophysical, physical, or sensor data analysis, including
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based in the School of Chemistry, University of Nottingham in the group of Dr Katherine Inzani. Candidates should hold a PhD (or close to completion) in materials science, chemistry, physics or similar
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based in the School of Chemistry, University of Nottingham in the group of Dr Katherine Inzani. Candidates should hold a PhD (or close to completion) in materials science, chemistry, physics or similar
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This research project aims to establish the theoretical and algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It
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bioinformatics. The successful candidate will join a team with a strong track record in developing computational tools and informatics infrastructure for metabolomics applications in toxicology, systems biology
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power in the ‘medicine, health and life sciences’ panel, including psychology, psychiatry and neurosciences. Within UCL, we are based at the Division of Psychology and Language Sciences (PALS), which has
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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over India with Machine Learning’ (HEPPI-ML), which is funded through the ‘Weather and Climate Science for Service Partnership ’ (WCSSP) programme. It is also linked to the National Institute for Health
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Position Details School of Computer Science Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,130 to £45,413 with potential
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About the Project We are seeking a talented and dedicated team of scientists, bioinformaticians and support colleaguesto join the ground-breaking PharosAI initiative – a £43.6M national programme co