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polygenic risk scores, rare variant burden scores, and integrative prediction models. Evaluate model performance and clinical utility. Identify therapeutic targets and causal risk factors for cardiovascular
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models ignore this exposome. In BEE, we will build explainable, physics-guided, GeoAI-driven models that: Predict acute and chronic NCD risks at the population scale Identify vulnerable neighbourhoods and
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 2 months ago
control theory (e.g., model predictive control, fuzzy control, etc.) # Excellent teamwork and communication skills in an interdisciplinary and international research environment # Motivation and self
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Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis
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research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish predictive models for evaluation
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they change through time. To translate eBird observations into robust data products we create custom modeling workflows designed to fill spatiotemporal gaps based on remote sensing data while controlling
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signaling models”. The scholarship is full-time for 2 years, with access starting in May 2026 or by agreement. The research will be carried out in the laboratory of Cemal Erdem at the Department of Medical
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, product management work, and and leadership responsibilities • Familiarity with artificial intelligence and machine learning approaches, including predictive modeling and precision analytics applied
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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already been awarded a PhD degree. Selection process You should submit your CV through a dedicated site: https://cv.newton-6g.eu/ Additional comments Position: Data-driven models for CF networks