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Field
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of a scientific mentor, you will gain experience and learn to conduct rigorous data analysis and cross-project data synthesis, identify critical technical and data gaps, and determine future applied
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interacts with the human body—making it a key factor in both product performance and consumer satisfaction. You will also apply statistical and machine-learning tools to explore how cotton fiber properties
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and processes; - Experience with machine learning and AI tools. Modes of Work Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work
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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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for Bayesian inference, inverse problems, uncertainty quantification, and scientific machine learning, with applications in environmental, scientific, and industrial imaging. The role/Te mahi We invite
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platforms, including robotic systems, laboratory automation, and AI/machine learning-assisted approaches for experimental design, optimization, and materials discovery. The research will target advanced
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proving, machine learning for reasoning, or neurosymbolic AI. Desirable Application/interview Further Information Grade Grade 8 Salary £48,822 - £51,753 Work arrangement Full-time Duration Until 30th
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, and openly release evaluation code. What is Required: A recent Ph.D. (within the last 1-2 years) in Computational Biology, Bioinformatics, Machine Learning, Computer Science, Statistics, or a related
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limited to: “Data Analytics for Social Research”, “Applied Analytical Statistics for Social Scientists”, “Machine Learning with Social Data” and “Social Networks Analysis”. The appointee should be prepared
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machine-learning, predictive-modelling or multivariate methods to behavioural and/or EEG data. Proficiency in R, MATLAB and Python. What we can offer In return we offer a generous pension, relocation