Bioinformatician (Assistant Scientist) in Cancer Informatics Shared Resource - UW Carbone Cancer Center

University of Wisconsin-Madison
Biostatistics and Medical Informatics
United States WI Madison


Position Summary:
The incumbent will be part of a small team supporting clinicians and scientists in processing and analysis of various next generation sequencing, proteomic, metabolomic, imaging, or clinical data.

The School of Medicine and Public Health has a deep and profound commitment to diversity both as an end in itself but, also as a valuable means for eliminating health disparities. As such, we strongly encourage applications from candidates who foster and promote the values of diversity and inclusion

Principal duties:
The incumbent will collaborate with University of Wisconsin Carbone Cancer Center (UWCCC) members to provide data
analysis and consultation for their research projects. It is essential that this individual be capable of working independently
and possess the ability to effectively troubleshoot and develop custom scripts and workflows. The successful hire will be
part of the UWCCC Cancer Informatics Shared Resources, and the Department of Biostatistics and Medical Informatics within the School of Medicine and Public Health.

The incumbent will be expected to independently select or develop the most appropriate methodologies for the clients, to
implement those methods and to effectively present their results.
Principle responsibilities include:

(75%) Partner with UWCCC collaborators and/or Informatics Core leadership to frame problems, outline solutions, select appropriate existing software or implement new tools, present results, write scripts for data preparation and informatics analysis, validate and implement scripts, and summarize results in appropriate reporting format.
- Perform comprehensive analysis of various biological data, including next generation sequencing data (DNA- Seq, scRNASeq,
- ChIP-Seq, ATAC-seq, RIP-seq, HiC), proteomics, metabolomics, and cell profiling, medical image data, and clinical data
- Integrate different types of data using statistical or machine learning techniques
- Work with other group members to design, develop, refine and improve bioinformatics tools for the analysis, synthesis and
- integration of diverse data sets
- Interact and collaborate with faculty and staff
- Sharing knowledge with others on the team
- Communicate methods and results effectively to a multi-disciplinary audience
- Manuscript preparation

(10%) Assist UWCCC collaborators with:
- Design of biological experiments
- Grant writing design

(10%) Keep abreast of current bioinformatics methodologies and attend UWCCC meetings not related to specific projects.

(5%) Other activities including adhering to all University, UWCCC, and Departmental policies and procedures.

Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals.

The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background - people who as students, faculty, and staff serve Wisconsin and the world.

For more information on diversity and inclusion on campus, please visit:


Ph.D. in statistics, computer sciences or related discipline. Expertise in bioinformatics, biostatistics, biomedical informatics, computational biology or a related field including biological sciences, statistics or computer sciences.

Two to three years of bioinformatics experience, post graduate work and/or professional experience. Working knowledge of bioinformatics computing, scripting languages, and biological data analysis applications. Significant experience in designing and implementing custom analysis pipelines for biological applications that include machine learning and/or statistical techniques. Experience areas of interest include single-cell transcriptomics, 4-C / Hi-C, medical image data analysis, genome assembly, variant or copy number variation detection, ChIP-seq, and other next generation sequencing analyses, microbiome analysis, expression profiling using RNA-seq, pathway/functional analysis, proteomic, metabolomics, cell profiling analysis, and multi-omic analysis in conjunction with clinical data.

The ability to work independently as well as collaboratively and to interact positively with a diverse group of researchers and their research. Attention to detail and ability to attain project milestones on time, to handle multiple projects and assignments, and to resolve problems required. Excellent oral and written communication skills. Ability to stay current on new biological and bioinformatics methodologies.

Start date

As soon as possible

How to Apply

Visit the listed URL. To begin the application process please click on the "Apply Now" button. You will be asked to upload a current resume/CV and a cover letter briefly describing your qualifications relevant to the position. You will also be asked to provide contact information for three (3) references, including at least one current or former supervisor.


Lily Kramer