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Internet Exchange (AMS-IX), and the Faculty of Science of the University of Amsterdam. About Research group The CWI Machine Learning research group focuses on how computer programs can learn from and
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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physics (e.g., Turing patterns). This will involve: (i) developing new analytical/theoretical tools for the study of reaction-diffusion systems, (ii) performing large scale, machine-learning-assisted
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
of English (Knowledge of German language not required) Additional experience in optics, machine learning, big data, in-strument design, image analysis, or electronics is a plus. Key responsibilities Design
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ophthalmological, neuroimaging and behavioral data, and incorporate deep learning methods to facilitate biomarker discovery and enhance predictive power. As a postdoctoral associate you will join a multidisciplinary
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, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research potential at the international level
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simulations using, e.g., COMSOL, Lumerical, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research
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are also developing novel machine learning methods to improve risk gene prediction and variant interpretation. This role will focus on the analysis of large-scale human genetics, scRNAseq, and proteomics
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The candidate will have a PhD or equivalent degree in bioinformatics, biostatistics, computational biology, machine learning, or related subject areas Prior experience in large-scale data processing and
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI