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The Bioinformatics Innovation Hub is a cross-Altos team working on challenging and exciting scientific projects and cutting edge technologies, requiring both the development and implementation of data processing workflows and advanced analytics of multi-modal datasets to unravel the molecular mechanisms underlying cellular rejuvenation and reprogramming.
Job Responsibility:
Collaborate closely with domain knowledge experts to plan and design studies to elucidate molecular phenotypes of cellular health, rejuvenation and reprogramming
Focus on FAIR data principles in the processing of internal and external NGS sequencing data, data organisation and metadata capture to enable efficient downstream data consumption
Generate insights and models from multi-omics datasets to understand patterns, trends and relationships within data to inform decision-making and solve problems
Develop and implement state of the art statistical, ML and AI methods for large scale data processing and analysis
Produce informative visualisations of complex analyses and embed these in automated and bespoke reports and interactive dashboards
Partner with other scientists to establish automated, robust and efficient analytical pipelines for reproducible research and to champion the integration of data science into biological discovery
Work with IT and data engineering teams to run analyses at scale in high-performance computing and cloud environments
Stay current with and adopt emergent analytical methodologies, tools and applications to ensure fit-for-purpose and impactful approaches
Requirements:
PhD in a quantitative field (e.g. computational biology, mathematics, physics) with significant biological background OR a PhD in the life sciences with significant computational experience
Extensive knowledge of multi-modal data analysis
Proficiency in Python and/or R, Linux. Hands-on skills using data science packages (for instance, Pandas, Scikit-learn, NumPy, Tidyverse, Caret)
Statistical analysis background
Excellent communication skills. Ability to present complex computational methods to non-experts
Established ability to translate biologists’/project team’s scientific questions into analytical strategies and methods
Strong collaboration skills and ability to work as part of a team in an international and interdisciplinary environment
Outstanding organisational skills and the ability to work independently
Familiarity with databases/resources relevant to drug discovery
Nice to have:
Knowledge of single-cell sequencing technologies and analytical techniques
Experience with Nextflow
Experience with long read sequencing (Nanopore, PacBio)
Experience with cloud providers (e.g. AWS)
Background in cellular rejuvenation and reprogramming
Familiarity with publicly available single cell data resources