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employing a combination of genetics, molecular biology, including Ribo-Seq, RNA pull-down and mass spectrometry, reporter assays in cells and tissues, and computational sequence analyses. This implies to work
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Student, you will be employed by ABC Labs while pursuing your PhD at KTH Royal Institute of Technology, giving you a unique opportunity to combine academic research with real-world impact. Project overview
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well as a highly collaborative research environment. For more information about Nathaniel Street’s research group, see: https://www.umu.se/en/staff/nathaniel-street/ Project description Establishing robust
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of pancreatic cancer. This group is led by Associate Senior Lecturer Dr. Qiaoli Wang, as part of the SciLifeLab & Wallenberg National Program for Data-Driven Life Science (DDLS) . Group members are enrolled in
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technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource hosted by Karolinska Institutet, KTH Royal Institute of Technology, Stockholm
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description Quantitative analysis of lipid nanoparticles (LNPs) using Cryo EM is challenging due to heterogenous
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, Computer Science, Data Science, Engineering, Physics, or equivalent Extensive (5+ years) experience of applying and/or developing advanced machine learning and AI methods in internationally competitive life science
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Centre (DC), which is responsible for IT-related matters and research data management for SciLifeLab’s technology platforms and other SciLifeLab-organised programmes and activities, including the national
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part of the SciLifeLab and the research school of the Wallenberg National Program for Data-Driven Life Science (DDLS), within the research area Cell and Molecular Biology. To achieve this, the doctoral
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Collaboration Conduct research together with academic, industrial, and healthcare partners in a highly collaborative environment. Who we are looking for A highly motivated PhD candidate excited by computational