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models using sophisticate genetic tools, in vivo time-lapse imaging and multi-omics methods to decipher the underpinning mechanisms of regeneration. Our findings provide new targetable mechanisms
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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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). We are seeking a highly motivated researcher to join our team. We use a wide range of molecular, cellular, transcriptomic, and advanced imaging techniques, in combination with ex vivo and in vivo
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cytometry, cell biology, metabolic assays, imaging and next generation sequencing to understand the molecular mechanisms involved in the regulation of immune cell function. The researcher (position 1) will
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microbiology, computer science, or bioinformatics (or a related field). Prior experience in R and coding is expected. Experience in analysing high-throughput sequencing data is a bonus. Excellent communication
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(or most) of your code may be open source and may be added to your public CV, depending on the needs of researchers. Fixed-term contract until 29.2.2028. All other standard benefits of Aalto as an employer
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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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of offers available1Company/InstituteUniversity of TurkuCountryFinlandCityTurkuPostal Code20014Street20014 University of Turku, Finland Contact City Turku Website http://www.utu.fi/en/ Postal Code FI-20014
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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
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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