Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) need to accelerate R&D by leveraging data and novel computational models. The new Computational Sciences Center of Excellence (CoE) aims to harness the transformative power of data and Artificial Intelligence (AI) to assist scientists in delivering more innovative and transformative medicines. The Analytics and Workflows group specifically needs to transform complex data into actionable insights for drug discovery and development, bridging the gap between data generation and biological interpretation.
Requirements
- expert knowledge of a modern bioinformatics workflow language (WDL, Nextflow, CWL or snakemake) and have deployed workflows in HPC or cloud environments
- expert in variant calling and variant interpretation from short and long reads using traditional and novel deep learning methods.
- successfully analyzed large cohorts using an automated workflow system and were involved in all aspects of the process from data acquisition, over workflow development to data processing and interpretation
- successfully delivered multiple software projects throughout the whole development cycle (planning, implementation, testing, release, maintenance) following modern software development practices
- strong experience in the use of a high-level, object oriented programming language such as Python, Go, R or Java and a strong understanding of Linux/Unix
- knowledge of best practices for software engineering including but not limited to IaC, CI/CD, and software containerization
- able to break down large problems into smaller software components and can develop them independently or as part of a large team
Responsibilities
- establish a suite of workflows and tools for the characterization of cell lines for our growing cell therapies portfolio
- evaluate, refine, and productionize genomic workflows and incorporate the results into our data platform
- make use of and are an expert in state of the art variant calling workflows and can interpret the results in a variety of biological contexts
- create automated reports and sophisticated data bases and tools allowing for deep analysis of cell lines
- confidently evaluate and combine open-source, commercial and in-house developed solutions
- collaborate with interdisciplinary teams of Software Engineers, Computational Biology and Data Scientists to develop scientific workflows and tools that make this data available to machines and humans using a variety of interfaces
- develop, deploy and optimize solutions on several levels of the software stack
Other
- You have a PhD in Software Engineering, Computer Science, Bioinformatics, or similar and 2 years of relevant experience in a clinical, academic or commercial setting. Alternatively, a Masters degree or equivalent and at least 5 years of relevant experience.
- You are comfortable working both independently and collaboratively, and with handling several concurrent, fast-paced projects.
- You are able to execute technical projects at global scale, across multiple teams and time zones.
- You have a strategic, analytical mindset and ability to innovate using technology to advance business goals.
- You have strong communication skills and can untangle and discuss complex technical tasks.
