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activities under the supervision of João Lacerda: Optimization of T cell therapies Phenotypic characterization of T cell population by flow cytometry Development of in vitro cancer models to study CAR T cells
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patients with early DKD and matched healthy controls. ▪ Development of an AI-driven digital African twin model capturing population-specific molecular heterogeneity, disease trajectories, and predictive
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contract model are those approved under the University of Coimbra's Research Grant Regulations. Where to apply Website https://apply.uc.pt/ Requirements Research FieldOtherEducation LevelMaster Degree
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. This role focuses on developing and applying AI and deep learning techniques for analyzing high-dimensional omics data, identifying predictive biomarkers, and understanding cancer heterogeneity. Projects
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-0831 Description of Work: At the Digital Twin Innovation Hub, we are developing infrastructure for the construction, simulation, analysis, and visualization of a human immune system model that represents
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., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves
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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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of developing a digital twin model of renewable energy generators”, 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), DOI: 10.1109/ISIE.2019.8781529 [4] https://uk.mathworks.com
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data · Demonstrated expertise in causal inference and high-dimensional risk adjustment/predictive modeling · Clear scientific writing and communication, an ability to work both independently and in teams
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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