24 engineering-image-processing-phd Postdoctoral research jobs at UNIVERSITY OF HELSINKI
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The Faculty of Social Sciences at the University of Helsinki invites applications for the position of POSTDOCTORAL RESEARCHER ON Aquatic Science and Technology Studies and More-than-human relations
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, developmental biology, genetics, biomedicine, or another appropriate field. Previous experience in confocal imaging and image analysis, scRNA-seq data analysis, or genetically engineered mouse models is
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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with
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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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breeding procedures for testing hypotheses arising from the analyses. Are you a technology wizard, determined to apply your skills in something that really matters? Or, alternatively, you have a solid
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/researchgroups/nuclear-organization-by-actin) . We are seeking a motivated researcher to join our team in the field of cell and molecular biology. By combining advanced imaging techniques with functional genomics
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include one or more of the following: Characterization and gene editing of cancer organoid cultures Use of genetically engineered mouse models to understand microbial adaptations Analyzing the cancer
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investigation and will develop an advanced computer modeling framework. By simulating processes at various scales, from the atomistic to continuum, we aim to reveal how temperature and saturation fluctuations
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% of annual working time). Requirements and eligibility criteria The Postdoctoral Researcher should have a PhD degree in computer science or bioinformatics (or related fields) with an emphasis on computational
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morphology imaging, and spatial transcriptomics—to identify altered cell states and mis-patterning events. The aim is to integrate computational and experimental approaches, including validation in vivo