The Howell Lab is seeking a Research Data Analyst to join our research in the genetics and genomics of neurodegenerative diseases including Alzheimer’s disease and glaucoma. This position will be part of our ongoing studies which seek to leverage complex multi-omics experiments to probe drivers of neurodegeneration and identify potential treatments.

This position will include curating current and historic datasets for data storage and sharing. Further, this position will analyze a wide variety of datasets (e.g., single cell RNA-seq/proteomics, spatial transcriptomics, and imaging data) for current and new projects. These analyses encompass a range of computational approaches including big data analysis through dimensional reduction and inference of disease relevance by comparison to matched human data. This position will network with members of the Computational Sciences and IT departments to disseminate data, analyses, and assist with visualization to facilitate broader community access. We are dedicated to open science and establishing an inclusive culture to expand our vision of scientific progress and encourage data usage.

What You'll Contribute

• Collating and annotating diverse datasets – both historic and newly generated
• Mining genome-scale data and interpreting results.
• Performing statistical analysis, algorithm implementation, data visualization, and bioinformatics programming; packaging and interpreting results.
• Developing pipelines for data analysis of new data types.
• Coordinating data analysis across multiple projects.
• Mentoring junior-level colleagues.
• Assisting in research planning.
• Assisting in data dissemination.
• Contributing to publications and presenting at seminars and conferences.

What You're Good At

• Master’s in the Computational or Biological Sciences. Incumbents who have not achieved a Master's degree may compensate for lack of a degree with a Bachelor's degree and at least 1-2 years of professional bioinformatics work experience.
• Experience with R is required, other languages such as Python are recommended
• Experience with algorithm development in areas such as machine learning, genomics, statistics
• Experience with genomic data is strongly recommended
• Knowledge of genetics, neuroscience, and neurodegeneration are desired but not required
• Ability to read scientific literature in fields related to current projects.
• Ability to contribute to scientific presentations and manuscripts.
• Ability to work in a team science environment involving researchers across multiple organizations.
• Ability to lead projects/processes, working independently with limited supervision