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Field
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with Linux/Unix and HPC systems (SLURM) Experience with version control (Git/GitHub) Understanding of statistics for genomic analysis Preferred: Long-read sequencing analysis experience Proficiency in a
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across Linux and other operating systems. Experience integrating genomic data with structured clinical data and familiarity with clinical ontologies (e.g., HPO, SNOMED CT, ICD‑10). A solid understanding of
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across Linux and other operating systems. Experience integrating genomic data with structured clinical data and familiarity with clinical ontologies (e.g., HPO, SNOMED CT, ICD‑10). A solid understanding of
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expertise in object-oriented programming in Python, data modeling, and scientific workflows experience in collaborative Linux-based development using Git knowledge of Python-based type systems and schemas
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, or computational analysis. Experience with automated pipeline development, multi-omics dataset integration, and reproducible workflows. Advanced proficiency in R, Unix/Linux environments, databases, and version
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, or a related field. Strong experience in statistical modelling, machine learning/deep learning, genomics and multimodal biological, and biobank data analysis. Proficiency in R, Python, Perl, and Linux
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in utilizing machine learning libraries such as PyTorch, TensorFlow, and Scikit-learn. At least 2 years of experience working with Linux computing clusters. Ability to work independently and within a
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. Required competencies: Strong background in bioinformatics (e.g., R, Linux, Python). Experience working with large cohorts and high-dimensional data. Experience with microbiome analysis and/or GWAS
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sequence or structure analysis, machine-learning method development, and modern software engineering practices. They should be proficient in Python and Linux-based development, familiar with deep learning
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bioinformatics, computational biology, or a related field. Proficiency with Linux operating systems is essential, as is the ability to analyse and interpret large datasets and apply critical evaluation to current