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, integrate molecular, histological, and clinical data through machine learning (ML)/AI-assisted methodologies. Your expertise in ML (Random Forest, SVM, Fully Connected Neural Networks) will be essential
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develop a simplified model focusing on the leader stage. You will: Analyze experimental data and microscopic simulations Identify relevant physical features and parameters Apply machine learning techniques
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analyzing textual and visual content with supervised machine learning. Conducting focus groups with social media users to understand how this content may shape beliefs and attitudes about AOMs, a healthy diet
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Organisation Job description The advent of modern machine learning (ML) methodology is accelerating scientific progress by streamlining research across disciplines. In chemistry, it enables
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bioinformatics and proteomics approaches. You will analyze bulk and clonal protein expression data from large melanoma cohorts, integrate molecular, histological, and clinical data through machine learning (ML)/AI
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for the analysis and integration of –omics data. The group has a strong track record in (integrative) computational omics analysis, algorithm development, machine learning and scientific data infrastructure