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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 14 days ago
) at the IT4Innovations, at the Material Design group of Dr. Dominik Legut within the Modeling of Nanotechnology Lab, is open to applicants for studying MATERIAL PROPERTIES OF MAGNETIC MATERIALS by means of the spin
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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an emphasis on ecosystem dynamics, behaviour, spatial modelling and evaluation of ecological aspects of management measures. The candidate may start as soon as possible or after agreement. The position is
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stability prediction Collaborating closely with experimental researchers for iterative model refinement Publishing high-impact research at the intersection of AI and molecular design Supervising students
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
: 265566 Vacancy ID: PDS003971 Position Summary/Description: The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https
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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g
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evaluation of predictive models and statistical approaches to understand treatment outcomes. Integration of diverse data types to identify features associated with therapeutic response, resistance, or toxicity
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statistical and econometric modeling, scientific-oriented thinking, communication and team skills, with a PhD in the field of economics, marketing. As a member of the team, you will deal with challenging
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, particularly in the area of time series modelling, analysis, and interpretation of temporal variations Preparation of publications and conference presentations Analyzing regional patterns in Terrestrial Water
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their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in