The Division of Newborn Medicine is seeking to hire a computational scientist to lead data analysis across a range of projects in collaboration with faculty across the Division, focusing on genomics and biology associated with brain, lung, heart, and intestinal development and disease.
Requirements
- Advanced computational experience, including with R and Python, is required.
- Experience with data from single cell sequencing, RNA-seq, or spatial transcriptomics is a plus.
- Experience with machine learning.
- Analytical skills to resolve complex problems requiring the use of scientific, mathematical, or technical principles and in depth, experienced based knowledge.
- Comfortable with the use of high-performance computing infrastructure, Bash scripting, R, Python, and other approaches.
Responsibilities
- Perform detailed computational analysis of varied data types, including single cell/nucleus sequencing, genome sequencing, spatial transcriptomics, ribosome profiling, among others.
- Execute standard computational pipelines and customize as needed based on project goals.
- Works effectively in a high performance computing environment with multiple coding languages.
- Provides input to the overall research design to suggest techniques, maximize samples or refine data by the use of specialized techniques.
- Evaluates research data and initiates alternative approaches to improve quality of the results.
- Calculates, graphs and compiles data obtained, maintaining records and logs of work performed.
- Perform and interpret statistical analyses.
Other
- Highly organized, a strong communicator, independent and curious problem solver, and capable of managing several tasks simultaneously.
- Prepares articles and papers on specialized techniques.
- Communicates results effectively with stakeholders in a timely fashion, in both written and verbal formats.
- Manages time and responsibilities across multiple tasks simultaneously.
- Attends multi-disciplinary lab meetings of faculty in the Division and participates in discussion of methods and results.
- Collaborates effectively with lab members who have a range of familiarity with computational methods.
- Ability to communicate effectively both orally and in writing including assigning and distributing work, coaching, training and enforcing policies.
