Scientist III

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). 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)

Job Title: Scientist III (Bioinformatics/Computational)
Location: Ridgefield, CT 06877
Contract Duration: 12 Months

Duties:
As an active team member of the Computational Innovation department at 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)