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Squamous Cell Carcinoma Therapeutic Targets Using Systems-Level Machine Learning Based On Single Cell RNA Sequencing", implemented under Financing Agreement No. 760066/23.05.2023 The “Iuliu Haţieganu
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THE PROJECT PNRR" Lung Squamous Cell Carcinoma Therapeutic Targets Using Systems-Level Machine Learning Based On Single Cell RNA Sequencing", implemented under Financing Agreement No. 760066/23.05.2023
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and resistance. Through close collaboration between laboratory and clinical teams, our work bridges mechanistic immunology with real-world patient outcomes. To learn more about Hosoya Lab - https
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statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft matter and nanomaterials
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machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive models and digital decision-support
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or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
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biology. GBI researchers will also be supported by cutting edge facilities including mass spectrometry, flow cytometry, sequencing, automation, scientific computing, bioinformatics, and machine learning
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application and machine learning. • Author of at least 2 research papers in topics related to the project. • Knowledge on advanced control systems and optimization (please attach a description of your
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incorporate clinical, lifestyle, and nutritional factors to build predictive models through advanced bioinformatics and machine learning. By identifying molecular signatures that distinguish responders from non
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Chekouo and his collaborators within and outside the University of Minnesota. The research will focus on the development of Bayesian statistical/machine learning methods for the data integration analysis