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Field
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: Candidates for open-rank positions should hold or be nearing completion of a Ph.D. in business analytics, operations research, operations/supply chain management, machine learning, artificial intelligence
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diagnosis and prognosis technologies, and, consequently, improve maintenance decision making. Currently, machine learning exists as the most promising technologies of big data analytics in industrial problems
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analytics Exploring and implementing federated learning and privacy-preserving AI approaches for distributed clinical datasets Collaborating closely with data providers, clinicians, and technical teams
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metabolomics and novel physiological MRI technique development within a translational research environment bridging analytical bioscience and neuro-oncology. Research Environment The successful applicant for a 4
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sensing systems Design and validate machine learning models for predictive monitoring of physiological states Analyse large experimental datasets and quantify sensor performance (accuracy, robustness
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-compliant data infrastructures that enable secure data sharing, reuse, and AI-driven analytics Exploring and implementing federated learning and privacy-preserving AI approaches for distributed clinical
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physiological MRI technique development within a translational research environment bridging analytical bioscience and neuro-oncology. Research Environment The successful applicant for a 4-year PhD studentship
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outcomes research and real-world data analytics, with a strong publication record. Proficiency in advanced data analytics, machine learning, and statistical modeling. Job Description: The Department
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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early