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Your job We are looking for an enthusiastic postdoctoral researcher to expand and strengthen research on "Healthy Lifestyle through Data Science, Machine Learning, and AI". Are you excited about the
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Postdoc in Machine Learning for Oligopeptide Design (1.0 FTE) (V24.0584) « Back to the overview Job description The advent of modern machine learning (ML) methodology is accelerating scientific
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the “Translator” work package within the core research programme of CropXR. Our goal is to develop computational methods to translate integrated plant models between species, combining machine-learning inferred
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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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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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, 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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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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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