Cloud Pipeline Developer - Scientific Workflows

Description:
Project
The Big DipIR platform provides tools and infrastructure for managing digital imaging data assets following FAIR principles, supporting critical path research and development programs.
We're seeking a Computational Biologist to develop robust Python-based algorithms and analysis pipelines for processing biological imaging data on cloud infrastructure.

Essential Qualifications
Strong Python programming expertise with demonstrated experience in scientific computing libraries
Proficiency with cloud computing, particularly AWS (EC2, S3, Batch)
Understanding of containerization (Docker) and version control (GitLab)
Strong communication skills to work with multidisciplinary scientific teams

Preferred Qualifications
Experience with workflow languages (Nextflow, WDL, or Snakemake)
Background in high-performance computing or distributed systems
Experience with scientific data formats and metadata standards
Experience in image analysis or computational biology algorithms

Key Responsibilities
Design and implement scalable Python algorithms for biological image processing
Optimize computational performance of existing analysis pipelines
Create and maintain containerized environments for reproducible analysis
Collaborate with scientists to translate analytical needs into computational solutions
Develop automated testing and validation procedures
Document analysis methods and maintain technical documentation

Technical Environment
Primary language: Python
Cloud platform: AWS
Version control: GitLab
Containerization: Docker
Scientific Workflow Engineer