Postdoctoral fellow in Computational Biology and Systems Medicine | Oslo, Østlandet, Norway | University of Oslo

Position:	Postdoctoral fellow in Computational Biology and Systems Medicine
Institution:	University of Oslo
Location:	Oslo, Østlandet, Norway
Duties:	Our current projects aim at developing new computational methods and tools for (1) modeling enhancer-promoter interactions, (2) integration of multi-modal single cell data using deep learning, (3) fine-tuned analysis of genome-wide regulatory networks, (4) integration of patient-specific regulatory networks with multi-omic data, (5) modeling networks based on single cell and spatial transcriptomic data
Requirements:	We seek a highly motivated candidate with a track record of statistical models, network science, and/or computational tool development dedicated to the analysis of of high-throughput genomics data, comparative genomics, functional genomics, or a related field. The candidate should be excited about applying computational tools to answer questions in biology. The ideal candidate is collaborative and creative, has strong programming skills dedicated to the analysis of large-scale genomics data, and has a strong publication record. Experience with analysis of large-scale genomic data sets is a requirement for this position. Experience with data integration, machine learning, network science, cancer biology, and/or gene regulation is considered an advantage. The position is open to applicants with a PhD in computational biology, bioinformatics, biostatistics, cancer genomics, network science, or related fields

Text:	Postdoctoral fellow in Computational Biology and Systems Medicine Our current projects aim at developing new computational methods and tools for (1) modeling enhancer-promoter interactions, (2) integration of multi-modal single cell data using deep learning, (3) fine-tuned analysis of genome-wide regulatory networks, (4) integration of patient-specific regulatory networks with multi-omic data, (5) modeling networks based on single cell and spatial transcriptomic data We seek a highly motivated candidate with a track record of statistical models, network science, and/or computational tool development dedicated to the analysis of of high-throughput genomics data, comparative genomics, functional genomics, or a related field. The candidate should be excited about applying computational tools to answer questions in biology. The ideal candidate is collaborative and creative, has strong programming skills dedicated to the analysis of large-scale genomics data, and has a strong publication record. Experience with analysis of large-scale genomic data sets is a requirement for this position. Experience with data integration, machine learning, network science, cancer biology, and/or gene regulation is considered an advantage. The position is open to applicants with a PhD in computational biology, bioinformatics, biostatistics, cancer genomics, network science, or related fields