Sr Scientist, Quantitative Bioimaging
Core
Develop and apply quantitative imaging, computer-vision, and machine-learning approaches to characterize cellular and tissue phenotypes for immunology discovery research.
Role type
Senior Scientist, Quantitative Bioimaging (Hands-on IC)
Builds
Robust, reproducible image-analysis workflows and computational insights for biological models (co-cultures, organ-on-chip, organoids).
Domain
Biopharmaceuticals / Immunology / Computational Biology
Deliverable
production ML models | product features
Required skills
quantitative image-analysis, computer vision, machine learning, deep learning, Python (NumPy, pandas, Polars, scikit-learn, PyTorch), statistical analysis, high-content imaging data analysis, feature extraction, phenotypic profiling, image segmentation, object classification, data integration (multimodal datasets), quality-control frameworks.
Preferred skills
complex in vitro models (organoids, organ-on-chip), classical bioimage-analysis tools (CellProfiler, ImageJ/Fiji), foundation models, self-supervised learning, peer-reviewed publications.
Technologies
Python, NumPy, pandas, Polars, scikit-learn, PyTorch, CellProfiler, ImageJ/Fiji, confocal microscopy, high-content imaging.
Responsibilities
Develop and optimize imaging assays and quantitative workflows for 2D/3D cellular models; collaborate with wet-lab and computational scientists from design to data delivery; extract multiparametric features to characterize disease-relevant phenotypes; apply ML/DL methods to identify imaging biomarkers; integrate imaging data with multimodal datasets; establish quality-control frameworks for image and assay quality.
Seniority
Senior, hands-on IC
