Research Assistant in Machine Learning for Gene Regulation

• Curate, process, and analyze high-throughput sequencing datasets (ATAC-seq, ChIP-seq, RNA-seq) at scale from public repositories and in-house experiments
• Deploy, evaluate, and interpret cutting-edge deep learning models for sequence-to-function prediction
• Read literature and assist with design of analyses and experiments
• Manage computational cluster space and contribute to lab chores

• Bachelor’s degree in a relevant field (Biology/Genetics/Bioengineering/Computer Science or related) is required
• Strong programming experience with demonstrated ability to analyze large datasets independently
• Comfortable working in Linux/Unix environments and on computational clusters
• A 2-year commitment is strongly preferred

Experience with either bioinformatics pipelines or machine learning/deep learning frameworks is a plus

• flexible schedules
• affordable health, vision and dental insurance
• child care and student loan subsidies
• generous levels of time off
• 403(b) Retirement Savings plan
• Pension
• Tuition and certain License and Certification Reimbursement
• cell phone plan discounts
• discounted rates on T-passes