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dynamics, Numerical Modeling, Scientific Computing, Applied Mathematics, Computational Chemistry). Experience in reactive transport modelling and strong background in reactive transport processes. Experience
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, to uncover convergent gene regulatory mechanisms, with the goal of informing therapeutic strategies. Tasks The tasks will include one or more of the following: Analysis of data collected from developing
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microbiome from clinical patient samples Computational analysis and integration of functional microbial genomics datasets from next-generation sequencing methods. Supervision and teaching of students and
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-cancer data network analysis. The Kuijjer group, established in 2018 at the University of Oslo, has recently expanded to the University of Helsinki. The group specializes in developing computational
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approach that includes advanced bioimaging and image analysis, cell biology and genetics, and omics technologies. Qualifications We invite applications from candidates with a background in cell and
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. We require the candidate to have documented experience in either large-scale genomics data analysis with computational or approaches/biostatistics, or machine learning/deep learning. Experience with
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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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(DGL) at the University of Helsinki. Selection criteria We are looking for a candidate with expertise in quantitative big data analysis and a strong interest in developing regional data analytics methods
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(DGL) at the University of Helsinki. Selection criteria We are looking for a candidate with expertise in quantitative big data analysis and a strong interest in developing regional data analytics methods
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should hold a PhD degree in molecular biology, biochemistry, cancer biology or related fields. Expertise in biochemistry, transcriptomics, NGS data analysis and basic programming in R/Python is a pre