Precision Oncology Data Scientist — Cell Painting

Ntnu; Trondheim; On-site; NOK 600,000 - 730,000; Full time

Benefits offered by this job

Exciting international academic enviro

Job summary

NTNU is seeking a researcher in computational high-content imaging analysis to work on ERKetype project. You will analyze Cell Painting data from cancer models and develop reproducible Python pipelines to link imaging phenotypes with drug responses, collaborating with international partners.

The role requires a PhD and strong English, with opportunities to publish and contribute to consortium deliverables in a cutting-edge precision oncology setting.

Qualifications

• PhD or equivalent doctoral degree in a relevant field such as bioinformatics, computational biology, biomedical engineering, image analysis, systems biology, cancer biology, biotechnology, or computer science.

Responsibilities

• Analyze Cell Painting and high-content imaging data from drug-screening experiments in cancer cell lines, patient-derived organoids and tumouroids.
• Develop, run and document reproducible image-analysis workflows, including CellProfiler-based segmentation and feature extraction.
• Create Python-based pipelines for preprocessing, normalisation, batch correction, quality control, statistical analysis, visualization and interpretation of large-scale imaging data.
• Extract and interpret morphological drug-response signatures at single-cell and population levels.
• Integrate imaging-derived phenotypes with drug-response data and other omics data.
• Collaborate with SINTEF Industry and NTNU clinical partners and contribute to data management and reproducible research practices.

Skills

Python

Bioimage analysis

High-content imaging

Cell Painting

English

Image analysis

Reproducible research

Norwegian

Education

PhD or equivalent doctoral degree

Tools

CellProfiler

GPU workflows

Job description

NTNU is seeking a researcher in computational high-content imaging analysis to work on ERKetype project. You will analyze Cell Painting data from cancer models and develop reproducible Python pipelines to link imaging phenotypes with drug responses, collaborating with international partners.

The role requires a PhD and strong English, with opportunities to publish and contribute to consortium deliverables in a cutting-edge precision oncology setting.