ASST RES SCIENTIST

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How to Apply

A cover letter is required for consideration for this position and should be attached as the first page of your CV. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.

Summary

The Assistant Research Scientist will work closely with faculty, postdocs and students within the Pancreatic Disease Initiative and affiliated scientists, supporting multiple projects. The candidate will conduct data analysis as well as train students and postdocs in utilizing R to analyze data generated in the laboratories. The candidate should be proficient in analysis of bulk and single cell RNA sequencing, whole exome sequencing, and willing to expand their expertise to spatial transcriptomics and multiplex immunostaining analysis. In addition, other computational needs might arise in the future, thus willingness to learn new approaches and innovate is a plus. A key area of interest for the group is understanding cell-cell interactions across the spectrum of pancreatic cancer progression, from normal pancreas to metastatic cancer. The candidate will be mostly in person, to facilitate interactions with other team members. While flexibility on in person work is possible, the candidate should attend the weekly joint pancreatic cancer working group lab meeting as well as weekly meetings of the team working on generating and analyzing human data. The candidate will not be required to apply for independent funding, but will have the opportunity develop new areas of research and submit grant application in the future. The candidate is expected to participate in group retreats, and will have the opportunity to attend pancreatic cancer conferences annually. The candidate will also oversee data storage and data sharing across a collaborative multi-institution network.

Responsibilities*

The role of this position is to develop and implement data analysis pipelines for bulk RNA sequencing, single cell RNA sequencing, single nucleus RNA sequencing, whole exome sequencing. In addition, the candidate must we willing to train in spatial transcriptomics, TCR sequencing and  other related techniques. The candidate will work closely with team members and faculty members to design and implement analysis pipelines. In addition, the candidate will be overseeing data storage and be responsible for data deposition in public repositories (GEO, dbGAP) following publication. The candidate will participate in lab meeting, data discussions, contribute data analysis ideas and participate in the design and writing of manuscripts for publication. 

Required Qualifications*

• Must have a PhD in engineering, computer science, applied mathematics, statistics, or data analytics
• Data science publication record
• 10 plus years of experience
• Programming languages: R, Python
• Strong understanding of statistical principles
• Experience with AI and machine learning algorithms
• Data Visualization
• Strong experience using online bioinformatics tools: GSEA, DAVID, iDEP, BioJupies, EnrichR, Ingenuity Pathway Analysis (IPA), iPathwayGuide, iVariantGuide 

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.