1,604 data-"https:" "https:" "https:" "https:" "https:" "https:" "SciLifeLab" "IFM" "IFM" positions at Nature Careers
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with institutional and program guidelines. Successful nominees will be expected to start their position at the University of Lethbridge within 12 months of accepting the award. Position Information
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out more about our DEI work here https://group.springernature.com/gp/group/taking-responsibility/diversity-equity-inclusion For more information about career opportunities in Springer Nature please
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are expected to perform research and teaching in the following areas: Mathematics, Physics, Chemistry, Materials Science, Energy Science, Energy Engineering, Optics, Computer Engineering, Integrated Circuits
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faculty. Our current research focuses on industrial plant security, digital twins, synthetic data for machine learning in privacy research, formalisation of security risk management and security and privacy
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sequencing instruments into microscopes! Your mission You will join our team, a leading group in the field of DNA nanotechnology specialized in creating molecular tools for life-science research (http
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. This research project has a dual focus. On the one hand, you will be involved in analysis of spatial, single-cell and multi-omics data to efficiently characterize the different molecular layers. This will be done
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protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis .
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and share its commitment to building a strong community. Interested applicants should apply through the job posting: https://ukjobs.uky.edu/postings/611204. Please include curriculum vita and cover
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d’actualités en Biologie moléculaire et Physiologie cellulaire Th 4 h, Ex. 10 h For more information, please contact Prof. Benoit Vanhollebeke (Benoit.Vanhollebeke@ulb.be ) or see the full announcement: https
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Cell Biol 160, 223–251 (2023). https://doi.org/10.1007/s00418-023-02209-1 Virshup, I., Bredikhin, D., Heumos, L. et al. The scverse project provides a computational ecosystem for single-cell omics data