Summary:
Pay Rate : $ 102.00 on W2/Hr.
Job Type : W2 Contract
Duration: 12 Months +
We are seeking a motivated Computational Biologist with hands on experience to join our team dedicated to advancing our Cardiometabolic Disease (CMD) portfolio.
As a scientist in CMD, you will:
• Be part of creative and enthusiastic teams working on target identification and validation (TIDVAL) for heart failure, NASH, fibrosis, inflammation, obesity, retinal diseases, and vascular disease
• Work with dynamic cross-functional matrixed teams to support discovery activities.
• Be responsible to adapt pipelines and create data analysis solutions to analyze large scale omics data (transcriptomics, genomic, genetic, metabolomic, proteomic) for TIDVAL.
• Work with in-house, open-source and/or commercially available platforms for the processing and analyzing large datasets.
• Engage and collaborate with wet lab scientists on experimental design, data analysis and interpretation, and mechanistic understanding of target biology.
• Have a proven track record across a wide range of computational biological methods, including but not limited to: next generation sequence data analysis, especially bulk RNAseq and scRNAseq, and data mining
• Collaborative mindset with strong communication and presentation skills
Quals--
Education Minimum Requirements
• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genetics, Physics, or related field, with hands on experiences in NGS data analysis
Required Experience and Skills
• Hands on experience in performing analysis and interpreting biology with large-scale omics datasets including transcriptomics, single cell RNA-Seq is required, knowledge and experience in other omics modalities are preferred, including proteomics, metabolomics, lipidomics and epigenetics.
• Proficiency in at least one programming language, such as R, Python, Perl or MatLab
• Capable of prioritizing projects and providing high quality deliverables on time
• Demonstrated ability to provide technical support, perform translational research, and contribute to cross-functional projects.
• Effective written and verbal communication skills
Preferred Experience and Skills
• Experiences in machine learning and AI
• Capability of integrating multiple resources to strengthen research comprehensiveness.
• Experience in applying computational methods to problems in cardiovascular and metabolic disease.
• Familiarity with public databases and repositories of DNA and RNA profiling data
• Strong publication record
Note: Onsite candidates are preferred. Open to remote candidates if they meet all the required skills and experience and are right fit for the role. •
Last updated on Nov 15, 2023