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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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programming skills in Python (experience with MATLAB or R is a plus). Proven experience with deep learning and machine learning frameworks (e.g., TensorFlow, PyTorch). Background in computational modeling
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the Molecular and Materials design program (MMD Hub ) of the Faculty of Science at UvA. What are you going to do? The aim of the project is to use advanced Machine Learning techniques to predict the anharmonic
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with strong expertise in one of these categories: solid-state NMR; Quadrupolar solid-state NMR; Automated NMR analysis & machine learning; Lipid biochemistry (and chromatography knowledge in general
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affiliated knowledge institutes. Key areas of interest include Bayesian machine learning, probabilistic graphical models (factor graphs) and probabilistic programming. Where to apply Website https
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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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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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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
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project partnership, able to perform within project timescales. You should have project management skills demonstrable from previous project experience. Competences in data analytics, machine learning / AI
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; Demonstrated interest in research on the intersection of society and AI, preferably as it relates to forms of algorithmic bias; Experience with machine learning or computational modeling; Strong quantitative