Part-Time

National Science Foundation National Synthesis Center for Emergence in the Molecular and Cellular S…

Pennsylvania State University

Pennsylvania State University

No salary listed

Company Does Not Provide H1B Sponsorship

State College, PA, USA

In Person

In-person at NCEMS space, Benkovic Building, University Park; 20 hours/week.

Category
Lab & Research (2)
,
Required Skills
Python
R
Machine Learning
Linux/Unix
Requirements
  • Applicants must be full-time doctoral students at Penn State University Park.
  • Be in good academic and conduct standing.
  • Demonstrate strong interest in computational and data-driven molecular or cellular science research.
  • Experience with Python or R.
  • Familiarity with Linux.
  • Project experience and interest in computational biology, bioinformatics, genomics, pipeline development, or related quantitative research areas.
Responsibilities
  • Support community-scale synthesis research by contributing to one or more NCEMS Working Groups.
  • Process and analyze molecular and cellular datasets, including transcriptomics and gene regulatory data such as ChIP-seq, ATAC-seq, and Hi-C.
  • Develop, run, and maintain reproducible computational pipelines and workflows.
  • Integrate and analyze multi-omics or multi-modal datasets for synthesis research.
  • Contribute to additional project areas based on project needs, including methodological work in machine learning and scientific applications in proteomics, molecular dynamics, and evolutionary biology.
  • Produce and maintain well-documented code, notebooks, workflows, and other research outputs.
  • Provide weekly progress updates during scheduled meetings with mentoring research staff.
  • Prepare interim and final written reports or presentations as requested.
  • Participate in regular meetings with mentoring research staff, broader NCEMS research personnel, and Working Group members to review progress, address blockers, and align work with project milestones.
Desired Qualifications
  • Experience with machine learning applications.
  • Experience with multi-modal integration of common biological data types.
  • Experience with workflow languages such as Snakemake or Nextflow.
  • Proficiency in Python and R.
  • Experience with transcriptomics and other gene regulatory data, including processing from raw files.
  • Knowledge of basic applied statistics, including hypothesis testing and multiple testing correction.
Pennsylvania State University

Pennsylvania State University

View

Company Size

N/A

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A

Your Connections

People at Pennsylvania State University who can refer or advise you