Research Specialist I/II - Req: ID 2022-16150

Position Summary

The Pritykin lab in the Computer Science Department and the Lewis-Sigler Institute for Integrative Genomics seeks applicants for Research Specialist I / Research Specialist II. The rank and salary will be commensurate with experience. 

We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other quantitative backgrounds who are enthusiastic about bringing their expertise to addressing fundamental problems in biology and medicine using cutting-edge technologies.

The Pritykin lab (http://pritykinlab.princeton.edu) uses applied statistics, machine learning, and efficient algorithms to address fundamental problems in biology and medicine by integrative analysis of multi-dimensional data. We develop and apply computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on single-cell, spatial and genome editing technologies. We are driven by questions in regulatory genomics, cancer immunology, and genome editing.

For this position, we are seeking motivated and highly organized individuals interested in learning about and getting fully embedded into one or more of specific scientific directions of our lab. Successful candidates will be expected to be able to read scientific literature to obtain the necessary biological background and become familiar with one or more data modalities (bulk and single-cell RNA-seq, ATAC-seq, ChIP-seq, CUT&RUN, Hi-C, CRISPR screens) and datasets we and others have generated for our projects. In addition, the person in this position will need to become familiar with the computational methodology and pipelines to analyze such data.

Specific duties include:

Research assistance in computational biology:

  • Reading scientific literature and obtaining necessary biological background
  • Getting familiar with one or more data modalities (bulk and single-cell RNA-seq, ATAC-seq, ChIP-seq, CUT&RUN, Hi-C, CRISPR screens) and datasets we and others have generated for our projects
  • Getting familiar with computational methodology and pipelines to analyze such data
  • Implementing or adopting these computational methods and applying them to analyze and visualize data
  • Regularly discussing progress with collaborators within and outside the lab
  • Preparing figures, presentations, reports, publications with results

A successful candidate will have an opportunity to contribute to a range of exciting collaborative projects in the lab, and eventually develop and lead new projects. This position is an excellent training opportunity before graduate or medical school or for achieving other career advancement goals. We are happy to provide a supportive and productive research environment.

Essential qualifications:

  • A bachelor’s or master’s degree in a relevant field is required.
  • Programming in R and/or Python.
  • Practical experience with data analysis and visualization.
  • Basic math and applied statistics background.
  • Scientific research experience.
  • Excellent communication and organizational skills.
  • Strong attention to detail.

Preferred qualifications:

  • Experience in computational biology, bioinformatics, biological or health data analysis.

The position is open and review of applications will begin immediately. Appointments are for one year, with possibility for renewal pending satisfactory performance and continued funding. The position is subject to the University's background check policy. Please email Dr. Yuri Pritykin at pritykin@princeton.edu with any questions about the position.

*Applications should be submitted online at Princeton University's Careers Site (Requisition Number: 2022-16150).*

Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. EEO IS THE LAW.

Type: 
Staff