Jobs

Description

This is a remote role (east coast preferred) working 40 hours per week.

The manager would only like to see candidates with a PhD for this request.

Duties: 

• As an active team member of the Computational Innovation department client, 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)