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The Role The successful applicant will be responsible for the design, development, and implementation of deep learning and computer vision frameworks across a range of research projects
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efficiently engineering new therapies. To do that, we use the most disruptive technologies of the last 20-years: machine learning and synthetic biology. Our team is highly interdisciplinary, including
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Research Associate to work on an industry-focused supply chain modelling and analytics project. The post-holder will have expertise in optimisation modeling, machine learning techniques, excellent
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on large-scale analysis of complex traits, including Bayesian machine learning and linear mixed model approaches for trait prediction and association in high-dimensional genomic datasets, as well as methods
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work on large-scale analysis of complex traits, including Bayesian machine learning and linear mixed model approaches for trait prediction and association in high-dimensional genomic datasets, as
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for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in
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. The post-holder will have expertise in optimisation modeling, machine learning techniques, excellent programming skills, simulation modeling and a strong track record of developing both academic and publicly
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mechanisms for grid-edge device federations participating in local and national flexibility markets. This will bring together research on power systems modelling, multi-agent control, machine learning and
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implementation of deep learning and computer vision frameworks across a range of research projects. This includes developing and training deep learning models for tasks such as scene understanding, object
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projects and publications from the group can be found here: https://www.kcl.ac.uk/research/pavri-group About the role The project is focused on combining artificial intelligence (AI)-based machine learning