Bioinformatics Scientist - III

Remote Full-time
Qualifications:
Education Minimum Requirements• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genetics, Physics, or related field, with hands on experiences in NGS data analysisRequired 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 skillsPreferred 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 recordNote: Onsite candidates are preferred. Open to remote candidates if they meet all the required skills and experience and are right fit for the role.Responsibilities: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

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