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molecular discovery. The position is ideal for a candidate who wants to turn deep mechanistic understanding into predictive models and closed-loop discovery workflows. Our lab develops and applies machine
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for a short-term 2.5-month postdoctoral position (full-time) focused on developing and validating machine learning models that predict soil health and crop performance. The position will exploit datasets
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of services. Data Science, AI/ML Modelling and Technical Research Support Support healthcare AI projects involving statistical modelling, machine learning, predictive analytics, natural language processing
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student to lead its theoretical side. We have predicted that stacks of planar oxocarbon radical anions – reactive molecules carrying both charge and unpaired electrons – should behave as one-dimensional
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designing and creating optimal processes and procedures to systematize the data reporting process. The incumbent will use advanced data modeling, predictive modeling, and analytical techniques to develop
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designing and creating optimal processes and procedures to systematize the data reporting process. The incumbent will use advanced data modeling, predictive modeling, and analytical techniques to develop
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Fundacion para la Investigacion e Innovacion Biosanitaria de Atencion Primaria | Spain | about 1 month ago
interoperability models and applied programming languages. • Development and validation of clinical data analysis models, including care pathways and predictive risk models. • Collaboration with other technical and
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the synthesis of functional inorganic materials. You will be developing modelling methods to explain and predict how molecular additives can be used to control the formation of particular phases and produce
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. Reporting to the Director of AIR, you will shape how AI is used to improve capability, efficiency, decision-making, and impact. You will set direction for advanced analytics, predictive modelling
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in vitro and preclinical in vivo DMPK data into predictive, clinically relevant models that ensure therapeutic viability and streamline the regulatory pathway. 3) Utilize data-driven simulations