Research Assistant - Naqvi Lab

Overview

The Naqvi lab at Boston Children’s Hospital and Harvard Medical School is looking for a highly motivated and enthusiastic Research Assistant to join our team. The Naqvi lab uses experimental and computational techniques to understand how transcription factors (TFs) regulate developmental gene expression, and how this process goes awry in disease. We are looking for a computational Research Assistant to join our team in order to drive forward ambitious projects applying cutting-edge machine learning models to high-throughput sequencing data obtained from TF perturbation experiments.

naqvilab.org for more information. This Research Assistant will be part of a dynamic and growing scientific team, with opportunities to shape the direction of an exciting research program at the intersection of gene regulation, machine learning, and stem cell biology. This is an inclusive and rigorous lab environment. The position is part of an intellectually stimulating scientific ecosystems of Boston Children’s Hospital and Harvard Medical School, with regular opportunities for seminars and coursework.

• 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
• This position will receive:
  • Hands on training and mentorship from the Principal Investigator
  • Substantial flexibility in defining specific projects/areas based on interests and expertise
  • Guidance and advice towards desired career goals, such as MD and/or PhD programs and industry roles

• 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
• Experience with either bioinformatics pipelines or machine learning/deep learning frameworks is a plus
• A 2-year commitment is strongly preferred