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The Institute of Human Biology (IHB) is seeking a Research Software Engineer (RSE) to join the Digital IHB (D-IHB) team. In this role, you will be pivotal in supporting our data challenges, specifically focusing initially on building robust image processing infrastructure to handle the massive data influx from our lightsheet microscopes becoming operational in 2026.
As part of the growing Software Engineering core, you will bridge the gap between complex biological data and scalable software solutions. While your immediate focus will be on bioimaging infrastructure, your role could evolve to lead the development of other modalities such as spatial omics integrations and tools, driving the future of digital biology at IHB.
You will work at the intersection of software engineering and biological discovery. Your primary responsibilities will include:
Design and implementation of scalable data processing and visualization to handle terabytes of biological data.
Optimize processing pipelines for High-Performance Computing (HPC) and Cloud environments (AWS), ensuring efficient resource utilization for large-scale datasets.
Support the integration of open standards (e.g., OME-Zarr) to ensure data accessibility and interoperability.
Champion software engineering best practices (reproducible builds & analysis, CI/CD, containerization, testing, and documentation) to transform research code into reproducible, maintainable software packages.
Support in identifying unmet digital needs and translate them into robust engineering requirements.
Contribute to upskill computational researchers by performing code reviews and teaching aforementioned best practices.
You are an experienced software engineer with a passion for science or a computational scientist with a passion for engineering. You understand the unique challenges of biological data and enjoy building tools that empower researchers.
An advanced degree (MSc or PhD) in Computer Science, Bioinformatics, Physics, Mathematics, or a related discipline is required.
Strong programming skills in Python with experience in relevant scientific stacks (e.g., NumPy, SciPy, Dask, Napari) is required.
Proficiency with source control (Git), CI/CD pipelines, and containerization (Docker/Singularity) is required.
Experience designing solutions that leverage distributed computing with e.g. HPC clusters or Cloud environments are required.
Solid background in mathematics, exploratory data analysis and statistics methodology and tools are required.
Excellent ability to communicate complex technical concepts to non-technical stakeholders (biologists) and translate scientific needs into engineering specifications is required.
Experience with the application of image processing methods on biological datasets, with an emphasis on microscopy is required.
Experience with data analysis in other modalities such as genomics, transcriptomics, or proteomics (including spatial variants of these and their integration with imaging technologies) is preferred.
Experience with out-of-core data processing and handling large data structures that exceed memory limits (using tools like Dask, Zarr, or similar chunking strategies) is preferred.
Ready to take the next step? We'd love to hear from you. Apply now to explore this exciting opportunity!
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