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Field
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, is organised as a section at the Department of Geosciences. PHAB’s main goal is to develop predictive models to identify habitable planets around other stars. Within three different research themes: (1
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, pharmacophore modelling, and molecular dynamics simulations to design novel GPR84 ligands with predictable signalling bias profiles. About the person: The successful candidate must have, and your application
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prompts Develop predictive models for sepsis, deterioration and ICU outcomes Create reproducible analysis frameworks using R/Python, GitHub, Quarto or R Markdown Produce real-time dashboards for ICU
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and increased uncertainty in life and non-life insurance modelling. data-driven prediction of insurance premiums and associated quantification of uncertainty. Qualifications and personal qualities
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algorithms for dynamic master selection, coordinating BESS, PV, diesel generators, and other sources. Implement predictive, rule-based, or optimisation-based control strategies using MATLAB/Simulink, Python
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main goal, based on detailed studies of Earth and the solar system, is developing predictive models to identify habitable planets around other stars. Within three different research themes: (1) Planets
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other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases
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position (100%, three years) is related to finance and insurance. The theme of the research project will lie within areas such as: simulation and risk modelling using advanced statistical and machine
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biology, and associated metadata, often across time, dose, or perturbation conditions, to enable phenotype-driven prediction and insight. Developing AI models to address translational questions, including
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assignment of a research grant, with one position(s), under the project CENTRO2030-FEDER-02359500, title ENDOSWEET - Sugars and polyols generated endogenously as predictive markers of Type 2 diabetes