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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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need to be able to be a role model in that sense. You must be very organized and systematic in your work. As an experienced researcher you will be expected to co-supervise the work of younger scientists
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. The role involves developing and maintaining systems and services for deployment, monitoring, and maintenance of AI models created in research contexts. In addition, it involves developing and maintaining
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, and develops various tools for bioimage analysis, mostly using machine learning and AI-based models. As a postdoc you will conduct research using various methods in cell-and molecular biology, but
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: CV including relevant professional experience and knowledge. Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not
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includes designing fusion proteins with various tags, producing viruses, transfecting human cells, and studying how these cell models are affected by small molecules and intracellularly produced peptides
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
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contribute new and better ways to analyse and interpret large-scale data. In your position, you will develop computational methods for cryo-EM reconstruction, heterogeneity analysis, and modeling of structural
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accessibility data will also be developed. The framework will be addapted and applied to spatial data to connect the GRN models to specific tissue phenotypes and to gain a better understanding of e.g. cancer