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for the aforementioned reactions. Based on the automatic reactor, an I-TR-NUS&TR-L running benchtop spectrometer, and machine learning algorithms, we will be able to achieve a higher yield and control the reaction to stop
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, or machine learning) Experience working with various animal models Ability to work in an interdisciplinary research environment Specific Requirements Programming experience (Python and R) Experience with
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circuit models and algorithms for estimating the charge, health, and power based on direct methods (e.g. open circuit voltage), model-based methods (e.g. Kalman filtering), data driven methods (e.g. machine
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. The ideal candidate should have a strong background in artificial intelligence and machine learning, with demonstrated experience in developing and training neural networks for predictive modeling. Position
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spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
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. About the role As Postdoctoral Researcher in Big Data for Cardiovascular Population Health, you will play a key role in applying machine learning, health statistics, and large-scale medical and population
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Hey machine learning enthusiast with a love for physics and
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qualifications. Our benefits include: • Generous employer contribution pension • 29 days annual leave plus bank holidays, along with Christmas closure • Ride to work and EV car scheme available For more
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employer contribution pension • 29 days annual leave plus bank holidays, along with Christmas closure • Ride to work and EV car scheme available For more information, please see University of Manchester
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics) • Multi-omics for non-cancer health screening applications, • Machine learning modelling