About the Role
We are seeking a creative and talented Scientist/Senior Scientist to support our understanding of disease mechanisms in Roche's Pharmaceutical Research and Early Development organization (pRED).
pRED is recruiting for the Systems Biology group, part of the Cardiometabolic, Immunology, Infectious Diseases, and Ophthalmology (CMI2O) Department.
Key Responsibilities
* In silico Experimental Design: Develop and operate data-driven research strategies.
* Rigorous Advanced Analytics: Explore data from disease areas of strategic relevance.
* Reproducible Reporting: Share emergent biological insights with stakeholders.
* Data Accessibility: Facilitate access to enterprise data and analysis tools for non-data scientists.
* Computational Analysis: Perform, customise, and/or develop computational analyses/algorithms for raw data from sequencing-based assays.
* High-Level Analysis and Visualisation: Pre-process raw datasets, enable interpretation, and deduce new biological insights.
* Collaboration: Analyse large-scale datasets with internal collaborators.
* Tool Validation and Optimisation: Validate and optimise emerging computational research tools.
* Research Collaboration: Support research collaborations with Roche experimental scientists.
* Tool Development and Maintenance: Develop and maintain tool applications (e.g. Shiny).
* Workflow and Pipeline Development: Implement novel and existing standardised workflows and pipelines.
* Data Management and Reporting: Manage data, report results, and maximise democratised access to data and analytics consistent with FAIR principles.
Requirements
* Education: PhD in a relevant discipline.
* Experience: Minimum of 5 years of postdoctoral experience, including professional experience within industry settings.
* Creativity and Flexibility: Ability to move across scientific domains, diseases, and biological scales with creativity.
* Programming Skills: R and/or Python programming skills required; working knowledge of Linux/Unix, HPC cluster environment, and basic computer systems administration.
* Experimental Science Experience: Experience working alongside experimental 'wet-lab' scientists and managing several concurrent projects with changing priorities.
* Data and Statistical Skills: Strong statistical, reporting, and data visualisation skills; essential data, code, and project hygiene.
* Genetics Foundation: Strong genetics foundation, including experience with Mendelian Randomisation, GWAS, and integrative analysis.
* Graph Theory Expertise: Expertise in graph theory and application of network-based approaches to biological data.
* Multimodal Data Integration: Expertise in the integration and visualisation of multimodal data from human clinical and/or model systems.
* Algorithm Development and Data Mining: Algorithm development, data mining, and statistical analysis of large datasets.
* Multimodal Data Handling: Experience handling, integrating, and visualising multimodal data.