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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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for the position of assistant professor in the project NCN MAESTRO "Challenging problems in partial differential equations inspired by cutting-edge algorithms in statistics and machine learning
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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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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do Reliably detecting persons is crucial
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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
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will include contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to be able to contribute in the following areas: Extend our
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provisions high-quality services in a cost-efficient manner. Performs surveillance activities and applies an epidemiological approach to problem solving. Utilizes externally defined criteria/algorithms
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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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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