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driving cancer heterogeneity and progression by integrating genomic data into genome-wide regulatory networks. Current projects include (i) modeling distal regulatory interactions, (ii) modeling networks
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models in collaboration with our international collaborators. You would also develop advanced image analysis schemes to analyse the experimental data. Your focus would be to investigate the effect
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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
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degree in conservation science, ecology, geoinformatics, mathematics, or other relevant fields. Applicants should have experience in statistics, programming languages and tools, primarily in Python and/or
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agent-based modeling or another relevant computational approach for the simulation of managed retreat. We look for a candidate in sustainability or environmental social sciences or a related field who
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to: Develop and apply machine learning models for analyzing complex datasets related to nature conservation. Establish and maintain code and data repositories to ensure efficient workflow and collaboration
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Run-3. Length of the contract is until 31.8.2029. We are seeking a talented and motivated doctoral researcher (PhD student) who recently completed their MSc degree in the field of experimental particle
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/or medication security and sustainability. The position is open to applicants with a PhD degree in law with a topic that gives a good background for a post doc in this area. The post doc is expected
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RESEARCHER / DOCTORAL RESEARCHER We are looking for a postdoctoral researcher to work on our projects that involve multiple sclerosis and myasthenia gravis. Also, applications for a PhD student position are
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the Kilpinen group (iPSC models of NDDs, scRNA-seq, CellPainting of in vitro neurons, multimodal data analysis) and the Kim group (single-cell multiomics, gene regulatory network modelling, smfISH, in vivo