As an active team member of the Computational Innovation department, the successful candidate will contribute to oncology drug discovery research through in silico data driven approaches. You will leverage multi-modal omics data analysis and collaborate with biologists to solve scientific challenges to advance drug discovery programs. This opportunity can be remote.
Duties and responsibilities:
- Support Oncology drug development efforts
- Identify, learn and apply emerging technologies in data science and its applications to novel cancer therapeutics discovery and development.
- Apply and develop innovative analysis approaches when standard methods are not adequate
- Identify and process publicly available and internally generated datasets using statistical and bioinformatics techniques to create meaningful biological insights
- Follow relevant scientific literature to ensure use of optimal methods and understand emerging practices across the field
- Interpret, report, and present analysis results, with a high level of integrity and ethics, to biologists and collaborators.
- Ensure FAIR data analysis with clear documentation and reproducibility
Skills:
- Programming experience with Python and R for bioinformatic data analysis in unix-like systems.
- Proficiency in working with bulk and single cell NGS data
- Experience with any of these topics is a plus: oncology or immunology knowledge, spatial transcriptomics, methylation, or liquid biopsy data analysis, public oncology database datasets (TCGA, GTEX, Human cell atlas, CZ CELLxGene Discover, Human tumor atlas network, etc)
- Proficiency in working with high performance computing clusters (HPC)
- Proficiency in biological pathway analysis
Education:
PhD degree from an accredited institution with experience in computational sciences or a related scientific discipline (e.g., Computer sciences, Computational Biology, Genomics, Biostatistics, Bioinformatics and Biological Sciences)
Pay Rate Range:
$45-50/hr depending on experience