Postdoctoral Research Fellow

Statistics Interest Group; Madison (WI); On-site; USD 60,000 - 75,000; Full time

Job summary

University of Wisconsin–Madison is inviting applications for a Postdoctoral Research Fellow in biostatistics, statistics, biomedical data science, and computational omics. The fellow will work with Dr.

Zhengzheng Tang and collaborators on methodological and applied research involving multi-omics data, including microbiome/metagenomics, genetics, and genomics. The Tang Lab at UW–Madison seeks candidates with strong quantitative training and a record of research excellence.

Qualifications

• PhD in a quantitative field (biostatistics, statistics, bioinformatics, computational biology, computer science, data science, or related)
• Strong training in statistical methods, machine learning, or quantitative biomedical research
• Experience with microbiome, metagenomic, genomic, genetic, or other omics data preferred but not required

Responsibilities

• Conduct independent and collaborative research projects
• Develop statistical and machine-learning methods for biomedical and omics data
• Implement computational tools and reproducible software
• Design and conduct simulation studies
• Analyze real-world biomedical, clinical, and omics datasets
• Interpret results and prepare manuscripts for peer-reviewed journals
• Collaborate with biologists, clinicians, and healthcare researchers

Skills

Strong written and oral communication

Independent and collaborative work

Solving real-world biomedical problems

Education

PhD in biostatistics, statistics, bioinformatics, computational biology, computer science, data science, or related field

Tools

R

Python

Job description

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University of Wisconsin-Madison – Postdoctoral Research Fellow

Company Name University of Wisconsin-Madison

Position Title Postdoctoral Research Fellow

Company Information

The Tang Lab at the University of Wisconsin–Madison invites applications for a Postdoctoral Research Fellow position in biostatistics, statistics, biomedical data science, and computational omics. The fellow will work with Dr. Zhengzheng Tang and collaborators on methodological and applied research involving multi-omics data, including microbiome/metagenomics, genetics, genomics, and related biomedical data.
The Tang Lab website is available at: https://tangzheng1.github.io/tanglab/

The University of Wisconsin–Madison is a leading public research university with a strong tradition in statistics, biostatistics, biomedical research, and interdisciplinary collaboration. The campus provides a vibrant research environment, excellent computational resources, and extensive opportunities for collaboration with biomedical scientists, clinicians, and public health researchers.

Duties and Responsibilities

The postdoctoral fellow will have opportunities to lead and contribute to projects in statistical methodology, machine learning, and biomedical data analysis. Potential research directions include, but are not limited to, microbiome and metagenomic data analysis, multi-omics integration, genetic and genomic studies, causal inference, interpretable machine learning, and methods for complex biomedical data.Responsibilities may include:

• Conducting independent and collaborative research projects
• Developing statistical and machine-learning methods for biomedical and omics data
• Implementing computational tools and reproducible software
• Designing and conducting simulation studies
• Analyzing real-world biomedical, clinical, and omics datasets
• Interpreting results and preparing manuscripts for peer-reviewed journals
• Collaborating with biologists, clinicians, and healthcare researchers

The position offers strong training in statistical methodology development, software implementation, collaborative biomedical research, and manuscript preparation. The fellow will have opportunities to lead first-author methodological papers and contribute to collaborative publications in high-quality peer-reviewed journals.

Position Qualifications

Applicants should have, or expect to receive, a PhD in biostatistics, statistics, bioinformatics, computational biology, computer science, data science, or a related quantitative field.

Preferred qualifications include:

• Strong training in statistical methods, machine learning, or quantitative biomedical research
• Proficiency in R, Python, or another programming language
• Experience with simulation studies, real data analysis, or software implementation
• Strong written and oral communication skills
• Ability to work independently and collaboratively
• Interest in solving real-world biomedical and public health problems

Experience with microbiome, metagenomic, genomic, genetic, or other omics data is preferred but not required. Candidates with strong quantitative training and an interest in biomedical applications are encouraged to apply.

Salary Range $60,000–$75,000 per year

The position is available immediately and will remain open until filled. The initial appointment is for one year, with the possibility of renewal for a second and/or third year depending on satisfactory performance and funding availability.