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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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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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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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Engineering, Biomedical Engineering or similar with experience in (medical) image analysis and/or machine learning. Affinity or experience with biomedical research (sequencing techniques, hisopathology) is
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of Computer Science, Computer Engineering, Biomedical Engineering or similar with experience in (medical) image analysis and/or machine learning. Affinity or experience with biomedical research (sequencing techniques
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development and pipeline development and deployment competence Expertise in biostatistics, including machine learning and AI Previous experience in teaching, student supervision, and course development is
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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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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