Post-Doctoral Associate - Bioinformatics & Computational Biology

University of Minnesota; Minneapolis (MN); On-site; USD 60,000 - 100,000; Full time

Job summary

An established research institution is seeking a talented computational scientist to advance spatial-omics technology and tackle complex genetic diseases. This role involves developing innovative methodologies, conducting integrative data analysis, and contributing to high-impact research publications. The ideal candidate will possess a recent PhD in a relevant field and demonstrate strong programming skills in R and Python. Join a collaborative environment where your work will significantly impact the understanding of genetic diseases and contribute to groundbreaking research in the field.

Qualifications

• PhD degree in a related field obtained in the last 1-2 years.
• Strong quantitative data analysis background and programming skills.

Responsibilities

• Develop novel computational methods to enhance spatial-omics technology.
• Conduct rigorous multi-modality data analysis from various sequencing technologies.

Skills

Machine Learning

Biostatistics

R Programming

Python Programming

Unix Shell

Data Analysis

Computational Genomics

Communication Skills

Education

PhD in Bioinformatics

PhD in Computer Science

PhD in Statistics

Job description

About the Job

Required Qualifications:

1. A PhD degree in a related field (Bioinformatics, Computer Science, Statistics, etc.) obtained in the last 1-2 years.
2. Strong quantitative data analysis background (machine learning, biostatistics, etc.) and/or computational genomics/genetics experiences (spatial transcriptomics, single-cell sequencing, high-throughput omics sequencing data analysis, TWAS/GWAS, etc.) or other relevant areas.
3. Strong programming skills (e.g., R, Python, Unix Shell).
4. Quick learning capability for new technologies and analytical methods.
5. Strong communication and interpersonal skills with a track record of collaborative work in a multidisciplinary research environment.

Job description:

Zhu's lab focuses on novel computational methodology design and integrative multi-modality data analysis to enhance spatial profiling technology and identify pathogenic upstream regulators.

Responsibilities:

1. Develop novel computational methods to enhance spatial-omics technology.
2. Advance understanding of complex genetic diseases such as fatty liver disease and diabetes.
3. Conduct rigorous integrative multi-modality data analysis from various sequencing technologies to elucidate biological regulatory mechanisms.
4. Publish high-impact research papers and present findings at academic conferences.
5. Manage and maintain software and databases for ongoing user support.