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Field
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research for digital security and is a pioneer in developing highly innovative concepts, algorithms and systems for anomaly detection, cyber threat intelligence, penetration testing and cryptography. Through
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econometric analysis and preparing results tables, managing large data sets, handling spatial data, applying machine learning algorithms, conducting computationally intensive statistical analyses, summarizing
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the total compensation value with benefits. Qualifications Experience developing software to take practical advantage of state-of-the-art ML algorithms and research results in AI. (Required) Experience
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dynamics or Hamiltonian eigenstates with classical and quantum algorithms Comparison of quantum algorithms with classical baselines Analysis and documentation of results What you bring to the table Student
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research across diverse basic and applied science and engineering domains. Responsibilities will include: ● Design, develop, and deploy ML/DL algorithms for domain science and engineering fields ● Support
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that the solutions provided are correct. It will involve a mix of algorithm engineering and formal methods, alongside more traditional software engineering activities. This project involves developing software which
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criteria Familiarity with the regulatory environment around Deep Learning or Machine Learning algorithms Experience applying quality system standards, software development standards and regulation, e.g. ISO
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, post-docs and interns collaborating across universities to build better algorithms, software tools and benchmarks to assess the safety of AI implementations at the software and hardware level. We
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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm
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University of Massachusetts Medical School | Shrewsbury, Massachusetts | United States | about 2 hours ago
and outliers in claims and develop trends and patterns for potential cases. Develop algorithms, queries, and reports to detect potential FWA activity. Analyze member records and claims data to ensure