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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in the Environmental Sensing and Modelling (ENVISION) unit
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 22 hours ago
# Development of high-accuracy atomistic models using efficient electronic structure methods, particularly for large-scale systems # Deepening the understanding of strongly correlated electron systems and real
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interaction with materials, as well as surface reaction kinetics based on kMC-type descriptions. The main activities include: (1) the development of efficient surrogate models of kMC-based surface kinetics
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academia, industry, and government that leverages the power of artificial intelligence (AI), robotics, materials sciences, and high-throughput chemistry to create self-driving laboratories (SDLs), also
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Person Registry (Person Dimension). Will also design, develop, and validate workforce data models that integrate traditional and AI-augmented approaches. Leveraging dimensional modeling principles (Kimball
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machine learning (ML) approaches offer a powerful framework for modeling complex catalytic materials with near ab initio accuracy while enabling simulations at significantly larger spatial and temporal
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expertise in engineering, materials, and data science, including AI/ML, to evaluate aerostructural and aeroelastic properties of aerodynamic systems, with a focus on high-fidelity modeling and simulation and
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, Salesforce, ServiceNow, Snowflake, and Azure-and designs future-state structures that support data products, analytics, automation, and AI/ML enablement. Establishes enterprise data standards, models
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Groundwater Geochemistry as Tracer of Critical Raw Materials (CRM) in the Per Geijer Mining District Luleå University of Technology experiences rapid growth with world-leading expertise within
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modeling framework, which we use to assess the industry transition of the three basic materials: steel, cement, and plastics. It consists of the dynamic material flow analysis model REMIND-MFA, tracking