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to or even much larger than the total sample size n. We refer to such “large p, small n” data as high-dimensional data. An enduring interest in statistics is to compare the covariance matrices of two high
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, Public Health, Climate Science, Data Science, or related disciplines. Demonstrated experience in managing large-scale data sets and conducting health-related research studies. Strong analytical skills with
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agentic architecture. With prior experience in AI security and AI agents, including prompt injections, data extraction, jailbreaking, poisoning and adversarial attacks, the candidate brings transferable
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synthesis of novel functional materials. Key Responsibilities: Implement data processing pipelines for materials informatics, including large-scale data mining, curation, and processing. Integrate
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using large language models, disease endpoint coding initiatives, and creation of common data model (CDM). He/she will also be expected to support/lead high-quality research in chronic disease
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++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large
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. Technical Skills: Proficiency in medical statistics, data science, and applications across various domains. Skills in processing and analyzing large datasets, data wrangling, visualization, big data analysis
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outputs across Projects 3-1 and 3-2 Manage and process large sets of operational data for case study analysis Contribute expertise in power grid optimisation to enhance planning models Participate in
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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with time-series data. The role involves conducting research on multimodal learning and leading technical development efforts within the project. Qualifications Applicants should meet the following