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Field
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years
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statistical modelling of high-dimensional data, e.g. penalised model selection and machine learning. Demonstrable understanding of RNAseq and gene expression analysis. Experience/skills handling and securely
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years
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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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SD-26045-RESEARCHER IN ADVANCED PLASMA-ASSISTED DEPOSITION PROCESS DEVELOPMENT FOR CATALYTIC THIN...
characterisation. Timely and high-quality contributions to project deliverables, reports, and milestones, including scientific publications. Team-oriented attitude, continuous learning mindset, strong documentation
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years
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London School of Economics and Political Science; | London, England | United Kingdom | about 1 month ago
/or Python. Willingness to learn unfamiliar tools as needed (e.g. GitHub, APIs, dispatch models). Familiarity with econometric techniques, especially panel data methods. Clear, concise written and
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., statistical modelling, Artificial Intelligence/Machine Learning) Experience in computational biology and bioinformatic analysis Proven ability to write detailed, technically accurate reports on complex research
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) Developing machine-learning based exoskeleton controllers to work across tasks 2) Designing and validating new robotic lower-limb prostheses 3) Exploring other high-risk high-reward research areas related