Computational Analyst (Neuroscience)

Role Summary

The Computational Analyst (Neuroscience) will collaborate with computational biologists and bioinformaticians to analyze high-dimensional OMICS data for target discovery and project support using pre-clinical and clinical data. They will refine analysis workflows and visualization tools (e.g., R Shiny) and communicate results to cross-functional teams.

Responsibilities

• Work closely with other computational biologists/bioinformaticians to implement and execute analysis and integration of high-dimensional OMICS data (genetics, transcriptomics, proteomics, metabolomics) for target discovery and project support using pre-clinical and clinical data.
• Refine and extend analysis workflows for data analysis, data visualization, and data tools (e.g. R Shiny) in collaboration with bioinformatics engineers.
• Communicate results to cross-functional teams in verbal or written form, facilitated by static and interactive data visualization.

Qualifications

• Required: Must possess a BS in Bioinformatics, (Bio)statistics, (Bio)Mathematics or related discipline, and 3 years of analyzing at least one OMICS modality (genetics, transcriptomics, proteomics, or metabolomics) from raw data to finished results; must have 3 years with each of: (i) coding in R or Python; (ii) generating interactive and static data visualization using R/Shiny or Python; (iii) applying statistical analyses, experimental design, regression and modeling to scientific questions; and (iv) translating data results, including informative data visualization, in a non-technical format for written and oral presentations to stakeholders.
• Alternate: MS in Bioinformatics, (Bio)statistics, (Bio)Mathematics or related discipline with 1 year of academic or industry experience analyzing at least one OMICS modality (genetics, transcriptomics, proteomics, or metabolomics) from raw data to finished results. Of academic or industry experience, must have 1 course or 1 year of (i), (ii), & (iii) (not (iv)).
• Experience may be gained concurrently. Would accept a combination of education, training and work experience.

Education

• BS in Bioinformatics, (Bio)statistics, (Bio)Mathematics or related discipline with 3 years of hands-on experience analyzing genetics, transcriptomics, proteomics, or metabolomics data, and 3 years of experience in coding (R or Python), data visualization (R Shiny or Python), and applying statistical analyses and data translation for non-technical audiences.
• Alternatively, MS in the same fields with 1 year of relevant experience and evidence of coursework or project work covering (i), (ii), and (iii) (not necessarily (iv)).

Skills

• Coding in R or Python
• Generating interactive and static data visualizations using R/Shiny or Python
• Applying statistical analyses, experimental design, regression and modeling
• Translating data results into non-technical formats for stakeholder communication