37 computer-programmer-"FEMTO-ST"-"FEMTO-ST-institute"-"FEMTO-ST" positions at University of East Anglia in United Kingdom
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, and edge computing, AASs are evolving into smart, interconnected solutions for addressing the dynamic challenges of modern cities. This project investigates how to coordinate these multifunctional
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programming skills in Python/MATLAB, and an interest in digital twin technologies, cybersecurity and machine learning. Entry Requirements Acceptable first degree: Computer Science or related disciplines
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Project Supervisor - Professor Rudy Lapeer The Birth4Cast “Digital Twin” aims to create a subject-specific computational biomechanics simulator of childbirth from prenatal fetal MRI scans
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confined battery geometries. Advanced modelling—including computational fluid dynamics (CFD) and transient thermal analysis—is required to accurately capture heat flux distributions, temperature uniformity
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-Markovianity. For sufficiently Markovian systems, the photon-photon correlations can be computed using the quantum regression theorem together with a Lindblad equation for atomic ensembles or a HEOM model of a
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research programmes and methodologies. The successful applicant will also be able to work collaboratively, supervise the work of others and act as team leader as required. Applicants will be able to carry
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observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
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sequencing and researching disease in patient cohorts, working with machine learning techniques and programming computers. The candidate will learn about different flavors of metagenomic sequencing, how
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decisions about personalised phage therapy. The expected workload is mainly computational, using bioinformatics analyses to investigate the microbiome and phageome with supporting laboratory work for DNA
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effects on the human host, either beneficially, such as antibacterial compounds, or negatively, such as toxins. Computational analysis of genomic data highlights a vast number of pathways to such molecules