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ultrahigh-throughput microfluidic screening to optimize mRNA for therapeutic purposes. mRNA libraries will be prepared by randomly combining different 5' and 3' untranslated regions (UTRs) identified
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move them between different environments. Perform extraction, normalization and transformation processes for large volumes of data. Integrate and harmonize data from multiple sources. Resolution
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, or computational research Strong programming proficiency in Python with scientific computing libraries Experience with machine learning frameworks Excellent communication skills for conducting seminars
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variety of experimental data, utilize different model structures/modeling techniques, are often closed source or coded in proprietary software packages with poor interoperability, and process experimental
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different disciplines, organisations and lived experiences to drive an internationally important civic health technology research and innovation cluster in Liverpool City Region. The Centre is a civic
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of deep learning algorithms. Outstanding programming skills in Python. Extensive experience working on one or more of the following areas: image processing, machine learning, and patient records. Track
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with transcriptomic analysis tools (e.g., Seurat, Scanpy, DESeq2). Experience with spatial transcriptomics and multi-modal data integration is highly desirable. Proficient in Python, R, and ML libraries
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values across different omics layers and platforms. Cross-omics data fusion and representation learning for comprehensive systems biology modeling. Identification of causal relationships and biomarker
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in unstructured texts. Writing of research articles and dissemination of the results obtained in different media. Where to apply E-mail vice.investigacion@unileon.es Requirements Research FieldComputer
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Bachelor’s degree (or higher) in bioinformatics, bioengineering, or related. Fluent in English, for both written and oral communication Experience in Python and/or R Experience with Linux/bash Previous