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sequencing, and with computer scientists at KTH in Stockholm, focused on developing scalable probabilistic machine learning techniques for online phylogenomic analysis and placement of DNA barcodes. You will
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bioinformatics, with a particular emphasis on performing analysis of high-dimensional data, which can be sequencing and/or imaging-based. Experience working with AI and machine learning approaches are considered a
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systems, and machine learning. While the initial focus of the position is on this project, we offer significant opportunity for the applicant to develop their own independent research trajectory in
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Python and MATLAB Documented experience with analysis of complex scientific data e.g. through machine learning What you will do execute experimental tasks, such as planning of experiments alone or together
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. Project overview The project involves applying advanced statistical analysis, machine learning techniques, and modeling approaches such as agent-based modeling to analyze diverse climate and socioeconomic
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experience with machine learning techniques in general and neural networks in particular will be highly beneficial.
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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to the application deadline. PhD in computer science, electrical engineering, biomedical engineering, or a related field. Experience in Python programming, natural language processing, and multimodal deep learning
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. The successful candidate will work on cutting-edge projects involving artificial intelligence (AI) and computational pathology, with a particular focus on developing and applying machine learning algorithms
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these datasets to detect chromosomal abnormalities and study their breakpoints. Using statistical methods and machine learning, we will explore how these structural variants arise and which recurring structures