Our client is a Boston-Based Biotech looking for a Principal Bioinformatics Scientist. Their mission is to enhance the well-being of patients by developing pioneering tRNA-based therapeutics that specifically target protein abnormalities. Our innovative approach to precision protein editing holds promise in treating genetically determined disorders, which contribute to approximately 10-15% of all human diseases.
As a member of the Data Science and Computational Biology team, the candidate in this position will play a crucial role in extracting valuable insights from data to drive drug discovery and preclinical development within various segments of our core platform.
Proficiency in applying machine learning or deep learning techniques to biological data will be highly advantageous. Applicants should be self-motivated individuals who thrive in a fast-paced and dynamic startup environment.
• Develop centralized, cloud-based solutions for data storage and efficient data access, specifically focused on public and private Next-Generation Sequencing (NGS) data.
• Streamline data import, aggregation, analysis, and visualization practices across all research and development (R&D) groups.
• Design and implement pipelines for the analysis of NGS data, enabling the assessment and prediction of drug effects both in vitro and in vivo.
• Take the lead in performing integrative analysis of multi-omics data, including tRNA-seq, bulk or single-cell RNA-seq, Nanostring, Ribo-seq, and proteomics, to generate valuable insights into the therapeutic mechanism of action.
• Utilize machine learning and/or deep learning approaches for clustering and predictive analysis as appropriate.
• Collaborate with project/program leads and Contract Research Organizations (CROs) to monitor data generation, importation, and analysis across different discovery and translation programs, ensuring the timely delivery of high-quality results.
• PhD in Bioinformatics with at least 5 years of experience in advancing discovery and preclinical research within the Pharma/Biotech industry.
• Extensive expertise in NGS data analysis, including bulk or single-cell RNA-seq, Nanostring, ATAC-seq, etc. Proficiency in multi-omics data integration, pathway and network analysis, dimensionality reduction, data visualization, and machine learning.
• Exceptional skills in manipulating and mining data from publicly available genomic, expression, and ontology databases such as GTEx, Human Protein Atlas, TCGA, GEO, KEGG, STRING, etc.
• Fluent in programming across diverse local or cloud computing environments, utilizing tools such as R, Python, Matlab, Nextflow, SQL, Github, etc.