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bulk and clonal protein expression data from large melanoma cohorts, integrate molecular, histological, and clinical data through machine learning (ML)/AI-assisted methodologies. Your expertise in ML
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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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immunology to understand fundamentals of adaptive immune recognition, to design next-generation therapeutics and diagnostics. Model antibody-antigen interaction using machine learning. Develop and apply
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composition, processing, and consumer responses. The AI system developed will utilize advanced techniques such as machine learning, natural language processing, and predictive modeling to detect potential
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), machine learning, network analysis, and econometrics. Proven ability using industrial ecology methods, such as LCA, MFA, and (MR)IOA to assess the scale and drivers of social, economic and environmental
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PhD* in a topic such as animal acoustics, machine learning, quantitative ecology, quantitative biology, signal processing or similar. Evidence of the ability to conduct high-quality research and write
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, mythical scenes of making, or depictions of making in sacred or military contexts). They will take into account (where applicable) how images interact with epigraphic frames and contexts of production and
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of making in ancient Roman visual culture (e.g. depictions of craftsmen at work, mythical scenes of making, or depictions of making in sacred or military contexts). They will take into account (where
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As a postdoc, the following is required: You hold a PhD in computer science, epidemiology, econometrics, machine learning, artificial intelligence, mathematics, data science, medical informatics, or a