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on bioinformatics analysis of spatial gene expression data as well as other modalities (i.e. microbiome; metabolites, proteins) generated using the Spatial Transcriptomics (ST) method, Spatial metaTranscriptomics
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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and integrative (proteo-)omics expertise in the lab, guided by leading experts in terminomics, systems-level data analysis, and structural bioinformatics. Your profile A PhD in biology, biochemistry
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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be
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is full-time for 2 years, with access starting in May 2026 or by agreement. Departmental specific information The research will be carried out in the laboratory of Cemal Erdem at the Department
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includes a combination of experimental work, data analysis, as well as interpretation and presentation of research results. The main part of the work for the advertised position involves studies of specific
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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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shared by Karolinska Institutet, KTH and Stockholm university. Your mission We are seeking a highly motivated postdoctoral researcher to join our team to develop new tools to analyze the sequencing data
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years according to central collective agreement. Full time position. Starting date as agreed. Placement: Uppsala For further information about the position, please contact: Ruisheng Xiong (e-mail
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cutting-edge, high-density data-driven research that impacts academia, industry, and policy worldwide. About the Programme Fellowship: each participant will benefit from a 36-month postdoctoral training