University of Minnesota

About the Job

Projects: The successful applicant will be expected to perform independent analyses of existing datasets in the following projects, with the order of priority set at the time of hire.

Project 1. LyRA (anticipate approximately 25% time on this project)

• analysis of NGS sequencing of circulating cfDNA.
• bulk RNAseq analysis.
• ATAC-seq analysis.
• 16S rRNA microbiome analysis.
• integrating multi-omics data.
• artificial intelligence (machine learning) applications.

Project 2. ORBIT (anticipate approximately 25% time on this project).

• single cell 3' longitudinal analysis (10X Chromium platform).
• 10X platform spatial genomics analysis (Visium and CytAssist).
• 10X platform single cell sequencing analysis (3’ and Flex).
• pseudo bulk analysis from single cell sequencing data.
• integrating multi-omics data.

Project 3. ORBIT Microbiome analyses (anticipate approximately 10% time on this project)

• 16S rRNA NGS data analysis.

Project 4. ORBIT Proteomics (anticipate approximately 5% time on this project)

• LC-MS/MS proteomics bioinformatics.
• multi-omics integrations.

Project 5. Osteosarcoma integrated single cell transcriptomics and spatial genomics (anticipate approximately 15% time on this project)

• analysis of single cell/single nuclei (10X Flex) and 10X CytAssist spatial genomics data from archival samples of primary and metastatic pediatric osteosarcoma.

Project 5. eBAT spatial genomics (anticipate approximately 5% time on this project)

• analysis of spatial genomics data of sarcomas from laboratory animals that received different treatments.

Project 6. Shine On (anticipate approximately 5% time on this project)

• cell ontogeny and functional assignment using existing atlases from single cell RNA sequencing.
• artificial intelligence (machine learning) applications.

Project 7. COED (anticipate approximately 5% time on this project)

• next generation exosomal RNAseq.
• artificial intelligence (machine learning) applications.

Mentoring. The applicant is expected to provide mentoring to graduate students in the Bioinformatics and Computational Biology program or other programs that are performing data analysis for projects in the Modiano lab (anticipate approximately 5% time on this project)

Qualifications

Required Qualifications

Hold a BS or BA (or equivalent) degree in or related to the biological sciences and more than an additional 48 months of dedicated experience in the field, for example, through

an advanced degree or work experience in bioinformatics and/or computational biology (i.e., at least 8 years of related education and experience in total are required to be eligible for the

position).

• Have previous experience analyzing relevant cancer datasets. Specifically, applicants with experience working on tumor/immune interactions, single cell and/or spatial transcriptomics, with canine datasets, and specifically addressing the biology and/or treatment of lymphoma, osteosarcoma, and/or hemangiosarcoma will be given preference.
• Have experience presenting cancer research to a relevant academic audience, in addition to having past (or pending) publication of work in a peer-reviewed journal and/or as part of a collection of abstracts from an accredited, peer-reviewed conference.

Required skills: The successful applicant will show:

• A strong command of biological principles, including evolution and natural selection.
• A basic understanding of neoplasia and immune function.
• Fluency in R and Python computing platforms.
• Significant experience with Seurat, Scanpy, tidyverse and ggplot2 R packages for bioinformatics analysis is required, as well as InferCNV, ClusterProfiler, and CellChat packages specifically for scRNAseq analysis.
• Essential experience mapping raw sequencing data to species specific genomes and performing analyses from open source and custom generated experimental cancer datasets, including one or more of the following (but not limited to these methods):

o single cell RNA sequencing, both cross-sectional and longitudinal.

o spatial genomics, including integration of functional regional relationships.

o bulk next generation RNA sequencing (RNAseq).

o cell-free DNA (cfDNA) / circulating tumor DNA (ctDNA) analysis.

o metagenomics (16S rRNA next generation sequencing and/or shotgun

metagenomic sequencing).

• Extensive familiarity and experience using MSI HPC for tumor data analysis, including:

o Job submission and scheduling with SLURM.

o Interactive HPC (Rstudio, Jupyter notebooks).

o Running/troubleshooting key MSI bioinformatics pipelines (CHURP, ClusterProfilerWrapper, etc.).

• Direct experience with bioinformatics analysis and handling of tumor/cancer datasets from more than one species.
• Proficiency with Linux and the ability to work from a command line.
• Outstanding laboratory etiquette and evidence of experience working with teams.
• Evidence of collegiality, specifically addressed in letters of reference.

Desirable qualifications and skills: In addition to the requirements described above, applicants possessing the skills listed below will be given preference.

• An advanced degree such as a Master’s of Research or equivalent in bioinformatics/computational biology with a capstone project from an accredited university program. Note that degrees awarded from online-only programs are insufficient to fulfill this qualification.
• Experience performing analyses from open source and custom generated experimental datasets or knowledge of one or more of the following (but not limited to these methods):

o whole exome/whole genome sequencing (WES/WGS).

o assay for transposable accessible chromatin using sequencing (ATAC-seq).

o proteomics (mass spectroscopy data).

o other ‘omics platforms (lipidomics, phosphoproteomics, metabolomics, etc.).

• A strong grasp of MySQL and an ability to operate/handle biological databases.
• Familiarity tracking code/document changes with version control (Git).

Pay and Benefits

Pay Range: $29/hr to $37/hr; depending on education/qualifications/experience

Time Appointment Category: 75%-100% Appointment (If job description above does not specify appointment or expected weekly hours, assume a 100% appointment.)

Position Type: Civil-Service & Non-Faculty Labor Represented Staff

Please visit the Office of Human Resources website for more information regarding benefit eligibility.

The University offers a comprehensive benefits package that includes:

• Competitive wages, paid holidays, and generous time off
• Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program
• Low-cost medical, dental, and pharmacy plans
• Healthcare and dependent care flexible spending accounts
• University HSA contributions
• Disability and employer-paid life insurance
• Employee wellbeing program
• Excellent retirement plans with employer contribution
• Public Service Loan Forgiveness (PSLF) opportunity
• Financial counseling services
• Employee Assistance Program with eight sessions of counseling at no cost
• Employee Transit Pass with free or reduced rates in the Twin Cities metro area

How To Apply

Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach a cover letter and resume. Applicants are asked to provide at least two and no more than four letters of reference from mentors or previous employers who can speak to the applicant’s scientific background, mastery of bioinformatics and computational biology, work ethic, collegiality, independence, creativity, and innovation.

Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.

To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-8647.

Diversity

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu

Employment Requirements

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

About the U of M

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

At the University of Minnesota, we are proud to be recognized by the Star Tribune as a Top Workplace for 2021, as well as by Forbes as Best Employers for Women and one of America’s Best Employers (2015, 2018, 2019, 2023), Best Employer for Diversity (2019, 2020), Best Employer for New Grads (2018, 2019), and Best Employer by State (2019, 2022).

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