Postdoctoral Associate in Machine Learning and Microbiome Engineering

Position Description

POSTDOCTORAL ASSOCIATE POSITION WITH PRECISION MICROBIOME ENGINEERING (PreMiEr)

Candidates are invited to apply for a postdoctoral research position at Duke University focused on machine learning, microbial genomics, and microbiome engineering.
The Postdoctoral Associate will lead research at the intersection of artificial intelligence and microbiome science, developing computational methods to identify health-relevant patterns in complex microbial communities using large-scale DNA sequencing data. The research will leverage DNA language models to characterize built-environment microbiomes and support the development of quantitative microbial risk assessment frameworks.

Specific research objectives include:

• Developing

and applying DNA language model approaches to identify microbial signatures associated with healthy and unhealthy built-environment microbiomes

• Designing

and evaluating machine learning methods for prediction and classification from metagenomic sequence data using sequence-based representations.

• Comparing

representation-learning approaches with conventional bioinformatics workflows and evaluating generalizability across independent studies, sequencing platforms, and environmental settings.

• Integrating

predictive models with broader PreMiEr efforts focused on microbiome monitoring, risk assessment, and precision microbiome engineering.

The Postdoctoral
Associate will be based in PreMiEr and supervised by Dr. Joshua Granek,
Assistant Professor of Biostatistics & Bioinformatics at the Duke
University School of Medicine, and Dr. Pixu Shi, Assistant Professor of
Biostatistics & Bioinformatics at the Duke University School of Medicine.

The Postdoctoral
Associate will be expected to develop novel computational methods, publish first-authored manuscripts in leading peer-reviewed journals, present research findings at scientific conferences, and contribute to collaborative interdisciplinary projects within PreMiEr. The scholar will work closely with biologists, engineers, microbiologists, and data scientists to prepare and analyze large microbiome datasets; implement and benchmark machine-learning methodologies; and support reproducible research practices through development of well-documented analytical workflows. There may be opportunities to mentor graduate and undergraduate researchers and contribute to educational and training activities within the Duke research community.

This appointment has an initial term of one year. Subsequent renewal will be considered based on funding, performance review, and approval from PreMiEr and the Pratt School of
Engineering. The anticipated start date is January 1, 2027.

MINIMUM REQUIREMENTS:

• Ph.D. (or equivalent doctoral degree) in

Bioinformatics, Computational Biology, Environmental Engineering,
Biostatistics, Computer Science, Genomics, Data Science, or a related quantitative field.

• Demonstrated experience conducting independent

computational or data-intensive research.

• Strong programming skills in R and/or Python.
• Experience analyzing high-throughput sequencing

or other large biological datasets.

• Evidence of scholarly productivity, such as

peer-reviewed publications, preprints, conference presentations, or open-source software contributions.

• Strong written and oral communication skills.
• Demonstrated ability to work effectively in

interdisciplinary research teams.

PREFERRED QUALIFICATIONS:

• Experience with

metagenomics, microbiome research, microbial genomics, or related omics datasets.

• Experience

with machine learning, deep learning, or representation learning.

• Familiarity

with high-performance computing environments and reproducible workflow systems
(e.g., Snakemake, Nextflow, Apptainer, or similar tools).

• Experience

with long-read sequencing technologies, including Oxford Nanopore and/or PacBio platforms.

• Experience

developing, documenting, and sharing reproducible computational workflows and research software.

REQUIRED MATERIALS:

• Cover letter
• Curriculum Vitae
• Names and email addresses of three references

Review of applications will begin immediately and continue until the position is filled.

Duke University is an Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, ethnicity, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation, or military status.

Duke University aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes.
To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.