16 finite-element-methods Postdoctoral positions at UNIVERSITY OF HELSINKI in Finland
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group, established in 2018 at the University of Oslo, has recently expanded to the University of Helsinki. The group specializes in developing computational methods to understand the regulatory mechanisms
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for an expert in quantitative methods and data analytics. The position involves designing and conducting research utilizing regional big data. The primary task is to develop the field of regional data analytics
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for an expert in quantitative methods and data analytics. The position involves designing and conducting research utilizing regional big data. The primary task is to develop the field of regional data analytics
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their impact on gene function and structure using a range of sequence analysis and comparative genomic methods. The projects will also involve programming for data collection and analysis. As a
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of Oslo, recently expanded to the University of Helsinki. The group specializes in developing computational methods to understand the regulatory mechanisms driving cancer heterogeneity and progression by
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offered a fully funded contract of up to 3 years. About the position The postdoctoral research position will require developing and applying cutting-edge machine learning methods to computer vision and
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expected to: Develop and apply quantitative methods specifically tailored to the goals of the BIOBANG project. Establish and maintain code and data repositories to ensure efficient workflow and collaboration
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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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well as cutting-edge systems biology methods, such as CRISPRi and nascent transcriptomics methods. The training could be furthered by research visits within our collaboration network of well-regarded laboratories
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in these diseases. The postdoctoral fellows will work on computational method development and data analysis for bulk and single-cell omics data from human patient samples. Individuals with a strong