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Field
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postgraduate qualification for Research Fellow. Proficiency with firmware extraction and reverse engineering. Proficiency with penetration testing techniques and tools. Proficiency with software scripting and
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deploying AI models for industrial inspection, predictive maintenance, or asset condition monitoring. Strong analytical, problem-solving, and software development skills. Ability to conduct independent
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sessions and initiatives. The fellow will be trained in the Gallery’s collections-management system (TMS), image and media databases, and other software systems as needed. Mentoring The fellow will be a
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good academic publication record Familiar with a few key engineering software such as MATLAB, Python, R-language, and ArcGIS, etc. Good to have knowledge of network analysis, machine learning, neural
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, including the production of analytic solutions, simulation studies, software tools and training materials. Role Summary Work within the specified NIHR-MRC funded research grant to develop sample size
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considered an advantage: basin modelling salt tectonics petrology geochemistry subsurface interpretation software (e.g., Petrel, Landmark DSD, etc.) Admission to the PhD programme requires that both your
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assessed according to the following weights and criteria: - Criterion 1: Absolute merit of the curriculum vitae: Overall evaluation of academic, software development, research and technical background
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engagement metrics, and statistical analysis Collaborate with interdisciplinary research teams including behavioural scientists, software developers, clinicians, public health experts, and national health
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. Experience in thermodynamic modelling and the use of simulation tools such as TRNSYS, EnergyPlus, Aspen, and Computational Fluid Dynamics software packages is essential. Instrumentation and experimentation
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scalable software and algorithms for genomic inference Collaborate with researchers across statistics, genetics, and computational biology Contribute to manuscripts, presentations, and open-source software