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, organoid-based models and in vivo cancer and infection models Integration and analysis of transcriptomics and proteomics datasets Establishment and maintenance of standardised experimental pipelines Data
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sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by
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on behavioural data. In addition to research, you will contribute to teaching (20%), providing opportunities for professional development. Your qualities We are looking for an enthusiastic new colleague who meets
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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. Additional Information Applicants must complete the Penn State application and must submit an application through Mathjobs.org (mathjobs.org) with the following materials in order for the application to be
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. It is situated in the Big Data Institute on the University’s Old Road Campus, giving it ready access to major medical research institutes such as the Clinical Trials Service Unit, the Oxford Centre
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. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University . About us A better future for everyone
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training pipelines using modern ML frameworks Generating data on miBd–pMHC interactions to guide iterative model optimization, espeicially for specificity Benchmarking AI-designed recognition modules against
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activities; and more! The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click
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practical experience of state-of-the-art molecular biology techniques and data analysis. In particular expertise in the following is essential : Genome editing, Epigenome editing, Off-target analysis, CRISPR