[Remote] Principal/Director, Computational Biology
Note: The job is a remote job and is open to candidates in USA. Verge Genomics is transforming drug discovery through artificial intelligence and proprietary human data. The Principal/Director, Computational Biology will lead the company's computational biology efforts, delivering insights to biopharma partners and driving their R&D decisions.
Responsibilities
ā¢ Deliver biological insights on therapeutic candidates and disease biology from the analysis of multi-modal data (transcriptomics, genetics, and clinical data)
ā¢ Translate high-level business objectives into a scientific workplan
ā¢ Synthesize diverse datasets to generate and evaluate hypotheses for target prioritization, mechanism-of-action identification, indication expansion, repositioning, biomarker discovery, and patient enrichment
ā¢ Present results to external stakeholders to drive pharma R&D decisions
ā¢ Develop and validate benchmarks to evaluate performance of AI models on translational tasks
ā¢ Interpret and analyze the output of AI foundation models
ā¢ Translate between biological domain knowledge and machine learning objectives
Skills
ā¢ PhD in computer science, computational biology, AI/ML, applied statistics, biophysics, or related field, or MS in related field with exceptional professional experience
ā¢ Experience applying computational methods (including probabilistic, statistical, and/or machine learning techniques) to analyze and integrate matched human clinical and molecular data
ā¢ Deep expertise with the multi-omic data integration (transcriptomics, genetics, proteomics, clinical data) and systems biology workflows (gene network, pathway enrichment analysis)
ā¢ Track record of delivering novel translational insights that have influenced pharma/biotech R&D decisions (e.g. target discovery, biomarker identification, patient stratification)
ā¢ Exceptional data visualization skills
ā¢ Experience leading cross-functional projects with multiple parties including biologists, engineers, AI researchers, and external collaborators
ā¢ Excellent coding skills in Python. A demonstrable portfolio (e.g., GitHub, research code, or shared notebooks) is highly preferred
ā¢ Domain knowledge with advanced AI approaches and experience applying them to a biological context
ā¢ Excellent communication skills, including explaining complex scientific concepts to cross-functional stakeholders using plots, documents, and presentations
ā¢ Ability to thrive in uncertainty with frequently changing priorities
ā¢ Deep alignment with our values
ā¢ A passion for making an impact on patients
ā¢ A demonstrable portfolio (e.g., GitHub, research code, or shared notebooks) is highly preferred
Company Overview
ā¢ Verge Genomics uses machine learning and human genomics to accelerate drug discovery. It was founded in 2015, and is headquartered in San Francisco, California, USA, with a workforce of 51-200 employees. Its website is http://www.vergegenomics.com.
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Responsibilities
ā¢ Deliver biological insights on therapeutic candidates and disease biology from the analysis of multi-modal data (transcriptomics, genetics, and clinical data)
ā¢ Translate high-level business objectives into a scientific workplan
ā¢ Synthesize diverse datasets to generate and evaluate hypotheses for target prioritization, mechanism-of-action identification, indication expansion, repositioning, biomarker discovery, and patient enrichment
ā¢ Present results to external stakeholders to drive pharma R&D decisions
ā¢ Develop and validate benchmarks to evaluate performance of AI models on translational tasks
ā¢ Interpret and analyze the output of AI foundation models
ā¢ Translate between biological domain knowledge and machine learning objectives
Skills
ā¢ PhD in computer science, computational biology, AI/ML, applied statistics, biophysics, or related field, or MS in related field with exceptional professional experience
ā¢ Experience applying computational methods (including probabilistic, statistical, and/or machine learning techniques) to analyze and integrate matched human clinical and molecular data
ā¢ Deep expertise with the multi-omic data integration (transcriptomics, genetics, proteomics, clinical data) and systems biology workflows (gene network, pathway enrichment analysis)
ā¢ Track record of delivering novel translational insights that have influenced pharma/biotech R&D decisions (e.g. target discovery, biomarker identification, patient stratification)
ā¢ Exceptional data visualization skills
ā¢ Experience leading cross-functional projects with multiple parties including biologists, engineers, AI researchers, and external collaborators
ā¢ Excellent coding skills in Python. A demonstrable portfolio (e.g., GitHub, research code, or shared notebooks) is highly preferred
ā¢ Domain knowledge with advanced AI approaches and experience applying them to a biological context
ā¢ Excellent communication skills, including explaining complex scientific concepts to cross-functional stakeholders using plots, documents, and presentations
ā¢ Ability to thrive in uncertainty with frequently changing priorities
ā¢ Deep alignment with our values
ā¢ A passion for making an impact on patients
ā¢ A demonstrable portfolio (e.g., GitHub, research code, or shared notebooks) is highly preferred
Company Overview
ā¢ Verge Genomics uses machine learning and human genomics to accelerate drug discovery. It was founded in 2015, and is headquartered in San Francisco, California, USA, with a workforce of 51-200 employees. Its website is http://www.vergegenomics.com.
Apply Now
Apply Now