Sr Scientist II, Computational Discovery Science
Core
Identify novel targets for cancer therapeutics by developing and applying computational methods to multi-modal clinico-genomic data and patient-derived organoid experiments.
Role type
Senior Scientist II, Computational Discovery Science
Builds
Novel molecular targets and biological patterns for cancer treatment
Domain
Life Sciences / Oncology / Computational Biology
Deliverable
production ML models | research
Required skills
Genomic data analysis, Machine learning, Statistical modeling, R, Python, SQL, Cancer biology, Immunology
Preferred skills
Patient-derived organoid (PDO) models, Single-cell RNA sequencing, Spatial transcriptomics, Drug development lifecycle, R package development, Client-facing consulting
Technologies
Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks, RStudio, tidyverse, ggplot, Git, Docker, AWS
Responsibilities
Utilize novel analytical methods on multi-modal data to identify targets in patient sub-populations; Apply in silico methodologies to Real-World Data to identify molecular and clinical patterns; Leverage multimodal data to compress complex data into joint embeddings for patient clustering; Use data from CRISPR and cell perturbation experiments in patient-derived organoids to validate novel targets; Independently execute complex translational research projects integrating molecular and clinical data; Communicate scientific plans and outcomes to cross-functional groups and external partners; Author abstracts, posters, and peer-reviewed publications.
Seniority
Senior, hands-on IC with leadership responsibilities
