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Computational Genomics Jobs (NOW HIRING)

Statistics Interest Group

The Liu Lab builds on a strong track record in AI-powered causal inference, Bayesian generative models, and computational genomics, with recent work published in leading journals, such as JASA ...

Meharry Medical College

Postdoctoral Fellow

Nashville, TN · On-site

$47K - $64K/yr

The position focuses on data analytics, computational genomics, machine learning, and the application of metagenomics to dental diseases. The Fellow will work closely with the PI on collaborative ...

Meharry Medical College

Postdoctoral Fellow

Campus, IL · On-site

$47K - $64K/yr

The position focuses on data analytics, computational genomics, machine learning, and the application of metagenomics to dental diseases. The Fellow will work closely with the PI on collaborative ...

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How much do computational genomics jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for computational genomics in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

What is a computational genomics job?

A Computational Genomics job involves using computational and statistical approaches to analyze genomic data. Professionals in this field develop algorithms, build models, and apply machine learning to interpret DNA sequences, gene expression, and other biological data. They work in research, healthcare, biotechnology, and pharmaceutical industries to advance precision medicine, drug discovery, and disease understanding. Strong programming skills, bioinformatics knowledge, and expertise in data analysis are essential for this role.

What does a computational genomics specialist do?

As a professional in Computational Genomics, your typical day may involve analyzing large-scale genomic datasets, developing and maintaining bioinformatics pipelines, and collaborating closely with experimental biologists and other computational scientists. You will often be tasked with interpreting complex biological data, troubleshooting data quality issues, and preparing detailed reports or visualizations of your findings. Additionally, you may participate in team meetings to discuss project goals, new research findings, or workflow improvements. This role requires balancing independent analysis with frequent interdisciplinary collaboration to ensure scientific projects progress efficiently.

What are the key skills and qualifications needed to thrive in computational genomics?

To thrive as a Computational Genomics professional, you need a strong background in biology, statistics, and computer science, typically supported by a relevant degree such as bioinformatics, genomics, or computational biology. Familiarity with programming languages (such as Python, R, or Perl), bioinformatics tools (e.g., BLAST, GATK), and platforms like Linux/UNIX is essential. Strong problem-solving abilities, effective communication, and the ability to work collaboratively with interdisciplinary teams are valuable soft skills. These abilities are crucial for accurately analyzing complex genomic data, developing robust workflows, and translating findings into actionable biological insights.

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Computational Genomics jobs near you
Infographic showing various Computational Genomics job openings in the United States as of September 2026, with employment types broken down into 5% Internship, 66% Full Time, 28% Part Time, and 1% Contract. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Postdoctoral Associate

On-site

Statistics Interest Group
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Posted 11 days ago

Job description

This is a current listing of job announcements related to Statistics.To submit a job for posting please use the Statistics Job Submission Form . Please note that jobs are posted within 24hrs of submission. If you have any questions, comments, or need to make acorrectionregarding your job announcement, please contact jobs@stat.ufl.edu .

Yale University, Department of Biostatistics – Postdoctoral AssociateCompany Name Yale University, Department of BiostatisticsPosition Title Postdoctoral AssociateCompany Information

The Liu Lab (https://liuq-lab.com) in the Department of Biostatistics at Yale University is looking for a highly motivated Postdoctoral Associate to join a growing research program at the intersection of generative AI, causal inference, regulatory genomics.
The Liu Lab develops statistically principled and AI-powered computational methods for analyzing massive, heterogeneous and complex biomedical datasets. We are building the next-generation computational frameworks that connect genetic variation, molecular regulation, perturbation response, and disease phenotypes. The overarching goal is to develop trustworthy AI systems that can move beyond prediction toward mechanistic understanding and causal discovery in biomedicine.
The Liu Lab builds on a strong track record in AI-powered causal inference, Bayesian generative models, and computational genomics, with recent work published in leading journals, such as JASA, Nature Communications, PNAS, Genome Biology. Yale offers an exceptional research environment, with close connections across biostatistics, computational biology, genetics, and medicine. The postdoctoral associate will also have priority access to the Yale Center for Research Computing, including a large-scale GPU infrastructure with 250+ GPUs, among them 80+ NVIDIA H200 GPUs and 60+ NVIDIA B200 GPUs.

Duties and Responsibilities

The postdoctoral associate will lead an ambitious project, focusing on building trustworthy causal AI systems to identify causal genes, regulatory elements, and molecular pathways linking genotype to phenotype. This is a highly interdisciplinary project in close collaboration with Dr. Hongyu Zhao (Biostatistics) and Dr. Steven Reilly (Genetics), integrating expertise in statistical genetics, computational genomics, and experimental genetics.
This position is ideal for candidates who want to develop cutting-edge computational methods on high-impact biomedical questions. The lab provides a highly interdisciplinary environment spanning AI, statistics, genomics, and public health. Postdoc will receive mentorship in method development, biological collaboration, grant writing, and career development. The goal is to help trainees grow into future leaders in academia or industry.

Position Qualifications

Applicants should hold or expect to soon receive a Ph.D. in computer science, computational biology, statistics, biostatistics, or a related field. Strong candidates will have experience in one or more of the following areas: deep learning, generative modeling, causal inference, foundation models or computational genomics. Strong programming skills in Python are expected, along with experience in PyTorch or TensorFlow and Linux-based high-performance computing. We especially value intellectual curiosity, creativity, strong communication skills, and enthusiasm for interdisciplinary research.

Salary Range 68500+

Interested applicants should send a CV, a cover letter briefly describing the previous research experience and future research interests, to Dr. Qiao Liu (qiao.liu@yale.edu).

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