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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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), 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
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machine learning or computational statistics or are eager to learn. Experience or affinity with constructing basic electrical circuits is a plus. You flourish in a team-centered, multicultural and
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handled, positioned, and assembled to function effectively. Current most advanced chip assembly machines run at tens of thousands of products per hour. In order to keep up with the market demands, micro
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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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or an interest in automation and programming. You know how to take the lead in your project, but you are also happy to support others in their work. Ideally, you have experience with machine learning
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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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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
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to perform within project timescales. You should have project management skills demonstrable from previous project experience. Competences in data analytics, machine learning / AI (for example in Python and