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When you join the UMass Chan Medical School team, you join us in advancing together to improve the health and well-being of our diverse communities throughout Massachusetts and across the US and the world. Together, we lead in education, research, health care delivery, and public service. Your life’s work is more than a career. It’s an expression of your passion, intellect, skill, and drive. UMass Chan's commitment to excellence, innovation, competitive benefits, and work-life integration will allow you to build a professionally rewarding career as we work together to better or improve the health of people around the globe.
Research projects in Dr. Zhu’s group include (1) development of bioinformatics algorithms and tools for integrative and interactive analysis of multi-omics data, (2) integrative analysis of multi-omics dataset for better understanding gene regulation and cancer etiology, and for biomarker discovery, and 3) development of algorithms and tools for designing effective gRNAs with minimal offtarget effects. Most recent relevant publications include Nature Methods 6(6):453-454. 2019. PMID: 31133757; Genome Res. 2019 PMID: 31201210; Nat Methods. 2018 Jan 03; 15(1):8-9. PMID: 29298290; BMC Genomics. 2018 03 01; 19(1):169. PMID: 29490630; Proc Natl Acad Sci 2019 PMID: 31068472; Cell. 2018 174(1):172-186.e21. PMID: 29958106. See https://profiles.umassmed.edu/display/129880 for details about the type of researches Dr. Zhu’s group does. Here is the list of algorithms/tools her group has developed including a dozen Bioconductor packages available at https://bioconductor.org.
This is a collaborative project consisting of a multidisciplinary effort spanning multiple laboratories across UMass Medical School. The efforts will focus on the development, enhancement and benchmarking of algorithms/tools for the integrative and interactive analysis and visualization of multi-omics data including various types of NGS data such as scRNA-Seq, ChIP-Seq, ATAC-Seq, RNA-Seq, NAD-Seq, Hi-C and PAS-Aeq/PolyA-Aeq.
These efforts will expose the successful candidate to cutting-edge technologies and latest researches in the field of biology and bioinformatics. The successful candidate will also gain experience on analyzing different types of deep-sequencing data. In addition, the successful candidate will be involved in developing/enhancing Bioconductor packages, which will broaden his/her exposure to one of the most widely used bioinformatics frameworks and will increase his/her visibility to one of the most active bioinformatics communities. In addition to publishing his/her own research papers, the successful candidate will have ample opportunities to publish joint research findings with our collaborators.
REQUIRED QUALIFICATIONS:
A successful candidate should have a Ph.D. in bioinformatics, computational biology, statistics, computer sciences or a related field. In addition, the potential candidate must have strong oral and written communication skills and be eager to present research results at national meetings. The candidate should be highly motivated with strong interests in bioinformatics research, have excellent publication record (including at least one first author publication) in peer-reviewed journals, have outstanding technical skills on bioinformatics analysis and programming. Prior experience with R/Bioconductor package development, algorithm/database/web development, and workflow language is strongly preferred. Experience with analyzing genome wide NGS data is a plus.
TO APPLY:
Interested applicants are invited to send (via e-mail) a letter summarizing current research activity, the reason for applying to the group and a statement of research interests, the curriculum vitae, and a list of three references to Dr. Zhu (julie.zhu@umassmed.edu).
Posting Disclaimer:
This job posting outlines the primary responsibilities and qualifications for the role but is not intended to be an exhaustive list.
Duties and expectations may evolve in response to the needs of the department and the broader institution.
In alignment with our commitment to pay transparency, the base salary range for this position is listed above (exclusive of benefits and retirement).
At UMass Chan Medical School, final base salary offers are determined based on a combination of factors, including your skills, education, and relevant experience.
We also consider internal equity to ensure fair and consistent compensation across our teams.
Please note that the range provided reflects the full base salary range for this position. Offers are typically made within the midrange to allow for future growth and development within the role.
In addition to base pay, UMass Chan offers a comprehensive Total Rewards package, which includes paid time off, medical, dental, and vision coverage, and participation in a 401(a)-retirement plan, with the option to contribute to a voluntary 403(b) plan.
