Post-Doctoral Associate - Bioinformatics & Computational Biology
University of Minnesota, Minneapolis, MN, United States
Job Details
Job ID: 358058
Location: Twin Cities
Job Family: Academic
Full/Part Time: Full-Time
Regular/Temporary: Regular
Job Code: 9546
Employee Class: Acad Prof and Admin
About the Job
Required Qualifications
A PhD degree in a related field (Bioinformatics, Computer Science, Statistics, etc.) obtained within the last 1-2 years.
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.
Strong programming skills: R, Python, and Unix Shell.
Quick learning capability for new technologies and analytical methods.
Strong communication and interpersonal skills and a track record of collaborative work in a multidisciplinary research environment.
Job Description
Zhu's lab is a dry lab. The research interests are mainly focused on the novel computational methodology design and integrative multi-modality data analysis to (1) enhance the spatial profiling technology and (2) screen the pathogenic upstream regulator.
Responsibilities
Develop novel computational methods to enhance the power of spatial-omics technology.
Develop novel computational methods to advance understanding of complex genetic diseases, e.g., fatty liver disease, diabetes, etc.
Conduct rigorous and reproducible integrative multi-modality data analysis (generated from spatially resolved sequencing, single-cell sequencing, long-read and short-read bulk sequencing, etc.) to shed light on the coordinated biological regulatory mechanism from different omics layers.
Publish high-impact factor papers and give presentations of novel research findings in academic journals and conferences.
Manage and maintain software/database for long-standing user support.
Pay and Benefits
Pay Range:
$62,232 - 75,564 (follows NIH stipend levels); depending on education/qualifications/experience
Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility.
Competitive wages, paid holidays, and generous time off
Continuous learning opportunities through professional training
Medical, dental, and pharmacy plans
Healthcare and dependent care flexible spending accounts
University HSA contributions
Disability and life insurance
Employee wellbeing program
Financial counseling services
Employee Assistance Program with eight sessions of counseling at no cost
Diversity Statement
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.
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Job ID: 358058
Location: Twin Cities
Job Family: Academic
Full/Part Time: Full-Time
Regular/Temporary: Regular
Job Code: 9546
Employee Class: Acad Prof and Admin
About the Job
Required Qualifications
A PhD degree in a related field (Bioinformatics, Computer Science, Statistics, etc.) obtained within the last 1-2 years.
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.
Strong programming skills: R, Python, and Unix Shell.
Quick learning capability for new technologies and analytical methods.
Strong communication and interpersonal skills and a track record of collaborative work in a multidisciplinary research environment.
Job Description
Zhu's lab is a dry lab. The research interests are mainly focused on the novel computational methodology design and integrative multi-modality data analysis to (1) enhance the spatial profiling technology and (2) screen the pathogenic upstream regulator.
Responsibilities
Develop novel computational methods to enhance the power of spatial-omics technology.
Develop novel computational methods to advance understanding of complex genetic diseases, e.g., fatty liver disease, diabetes, etc.
Conduct rigorous and reproducible integrative multi-modality data analysis (generated from spatially resolved sequencing, single-cell sequencing, long-read and short-read bulk sequencing, etc.) to shed light on the coordinated biological regulatory mechanism from different omics layers.
Publish high-impact factor papers and give presentations of novel research findings in academic journals and conferences.
Manage and maintain software/database for long-standing user support.
Pay and Benefits
Pay Range:
$62,232 - 75,564 (follows NIH stipend levels); depending on education/qualifications/experience
Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility.
Competitive wages, paid holidays, and generous time off
Continuous learning opportunities through professional training
Medical, dental, and pharmacy plans
Healthcare and dependent care flexible spending accounts
University HSA contributions
Disability and life insurance
Employee wellbeing program
Financial counseling services
Employee Assistance Program with eight sessions of counseling at no cost
Diversity Statement
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.
#J-18808-Ljbffr