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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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biological science subject High level analytical capability Ability to communicate complex information clearly Full working knowledge of informatic environments including R Extensive experience and fluency in analysis
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experience with coding in Matlab, Python, or R. Strong track record in computational science, image analysis, or mathematical modelling of complex systems. Evidence of publications in reputed refereed journals
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: 21st August 2025 Background To create and contribute to the creation of knowledge by undertaking advanced analysis and validation experiments within the MRC BioFlare research programme: Although outcomes
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Sciences . It includes mathematical and physical modelling, numerical simulations of materials and nanosystems, low-dimensional systems, quantum matter, statistical physics, and complex systems
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are provided in Arts and Humanities, Built Environment, Brain Sciences, Engineering Sciences, Education, Laws, Life Sciences, Mathematical & Physical Sciences, Medical Sciences, Population Health Sciences and
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded
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Researcher to join a cutting-edge project focused on the self-consistent analysis of black hole horizons and their observational signatures. This role offers the opportunity to work within a dynamic research
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John Williamson, and Dr Sebastian Stein. The job requires the proven ability to develop novel theory and build and evaluate working interactive prototypes involving complex computational models
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is a partner for the Alrek Health Cluster, Årstadveien, Bergen, and is supported by the Trond Mohn Foundation related to Complex Conditions and Ageing (CC.AGE). Read more about the project: https