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integrating gene expression, chromatin accessibility, cell morphology, and spatial data, we aim to uncover shared regulatory disruptions across neurodevelopmental disorders. Postdoctoral Researcher in Single
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at the Faculty of Medicine, University of Helsinki. The project will focus on using and extending deep learning-based approaches developed within the group to integrate bulk multi-omics cancer data. The Kuijjer
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profiling. By integrating gene expression, chromatin accessibility, cell morphology, and spatial data, we aim to uncover shared regulatory disruptions across neurodevelopmental disorders. Host institution and
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This project aims to identify the spatial genetic and adaptive dynamics of tumour microbiome in colorectal cancer. To do so, we will integrate single-cell genomics, transcriptomics and clinical data
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methods to understand the regulatory mechanisms driving cancer heterogeneity and progression by integrating genomic data into genome-wide regulatory networks. Current projects include (i) modeling distal
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R, algorithms and systems designed to extract insights from large datasets. Experience with integrating and analyzing diverse data sources, such as biodiversity (e.g., the IUCN Red List of Species and
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on Research Integrity (TENK) 3/2020 CV template (https://www.tenk.fi/en/template-researchers-curriculum-vitae ) Numbered list of publications following the Research Council of Finland format (https://www.aka.fi
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and analyses that can help investigate human-nature interactions to inform decision making. We carry out global to local analyses, by integrating traditional and novel digital data sources. Our research