178 engineering-computation-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"BioData" positions at University of Birmingham
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geography/remote sensing, ecology, statistics, engineering, quantitative social sciences, or a related discipline. Experience in developing models and mapping with real world data, with strong programming
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validation in representative environments. The successful candidate will gain expertise in electrochemical sensing, microengineering, and computational modelling, and will join an interdisciplinary research
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, statistics, engineering, data science, quantitative social sciences, or a related discipline. Experience in developing models & mapping with real world data, with strong programming proficiency in R or Python
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Engineering, Computer Science or a related discipline. You should be highly motivated, and would be able to work independently as well as collaborate with others with effective written/oral communication skills
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engines, alternative fuels, combustion optimisation, and powertrain control. As the automotive industry transitions towards electrification, integrating novel fuels—such as hydrogen, ammonia, e-fuels, and
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Background To create and contribute to the creation of knowledge by undertaking a specified range of activities within the research programme of the Elementary Particle Physics Group. To work on detector
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critical mass on distributed radar, which is currently supported by prestigious and large initiatives including QuSIT and a newly awarded Royal Academy of Engineering (RAEng) Research Chair on distributed
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Professional programme which provides all professional services staff with development opportunities and the encouragement to reach their full potential. With almost 5,000 professional services jobs in a wide
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Job Description Position Details School of Metallurgy and Materials, College of Engineering and Physical Sciences Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate