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perturb sequencing to establish foundational models to predict the effects of potential drug candidates on cardiovascular diseases. By combining genome engineering, functional genomics, and tissue models
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an ability to combine perspectives and quantitative methods from multiple scientific traditions is essential to gain insights and make predictions for systems characterised by many degrees of freedom and
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ACHILLES, which brings together a broad spectrum of expertise, including basic research to identify novel biomarkers and therapeutic targets, mathematical and computational modeling to predict disease
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
physics- and data-driven models that deal with microstructure/texture evolution during extrusion to predict material properties of extruded profiles Collaborate with other researchers and industry partners
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application. The ambition of this research is to understand, and even predict through modeling, the damage process of tuffeau limestone in its most damaging form of deterioration: spalling. The hydromechanical
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linear models Knowledge and implementation of machine/statistical learning methodology (predictive modeling workflow) R package development experience Demonstrated experience with Tableau (or Power BI
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building cutting edge machine learning techniques
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data to identify proteomic signatures and develop novel predictive models for Alzheimer’s, Parkinson, and Dystonia as well as to identify novel proteins and pathways implicated on disease pathogenesis
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the University of Porto (FEUP), under the scientific supervision of Professor Alexandre Ferreira. Grant duration: Initial duration of 3 months, with the predicted starting date in May 2026, on an exclusive basis
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: Initial duration of 6 months, with the predicted starting date in April 2026, on an exclusive basis eventually renewable but never exceeding the project duration. If it is not possible to ensure