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, Chapter 7, Section 39). Applicants must: Be proficient in at least one statically typed programming language. Have substantial experience of developing software (e.g. projects with > 10k lines of code
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computational free energy calculations. Familiarity with contemporary MD software packages and analysis tools is necessary. The candidate should demonstrate strong problem-solving skills, attention to detail, and
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new era of quantitative and predictive biology. Install, configure and maintain Linux servers (hardware and software) Manage clusters, software environments and automation tools (e.g. Ansible) Develop
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, bioinformaticians, and software developers, both within Clinical Genomics and in collaboration with healthcare professionals at Karolinska University Hospital and research groups at Karolinska Institutet. By applying
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using Cell Painting and high-content imaging. Deep learning and multivariate methods, both supervised and unsupervised. Development of software and pipelines for analysis of large-scale image data
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the research and education has a unique breadth, with large activities in classical scientific computing areas such as mathematical modeling, development and analysis of algorithms, scientific software
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bioinformatics pipelines for the metabolomics data analysis and visualization of metabolomics data, support the integration of software tools for data (pre-)processing, biomarker discovery, and predictive
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and proteomic data Knowledge of git, conda and similar Knowledge of workflow management systems such as Snakemake and Nextflow Experience of container software such as Singularity (Apptainer)/Docker
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image analysis software (e.g. Fiji, Napari, scikit-image). Familiarity with high-performance computing or cloud environments. Experience with multimodal or correlative imaging data (light/electron
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(MaxQuant, Proteome Discoverer, Peaks Studio, DIA-NN, HDX-Examiner, etc), MS RAW data analysis software (Xcalibur, Freestyle, etc.). Proficiency in protein-centric pathway analysis, enrichment, and network