Position Description

Research Associate in Venturelli Lab  

The Venturelli Lab at Duke University (www.venturellilab.org) is seeking highly motivated researchers or postdoctoral researchers with expertise in machine learning, deep learning, and/or nonlinear dynamical systems to join our interdisciplinary team.

Our research focuses on developing and applying computational frameworks—including machine learning, nonlinear dynamical systems, and hybrid physics-integrated machine learning models—to predict, analyze, engineer, and understand microbial community dynamics. Applications span precision medicine and built environment microbiomes, with a strong emphasis on active learning approaches to guide experimental design cycles.

In addition, we are developing deep learning models that map genetic information of microbial species to their functional capabilities, leveraging high-throughput experimental data to connect genotype to community-level function.

Responsibilities could include:

·       Develop novel computational, hybrid, and deep learning models of microbial communities.

·       Apply active learning strategies to optimize experimental design.

·       Integrate genetic and functional data using high-throughput experimental datasets.

·       Collaborate closely with experimental researchers to align computational predictions with experimental results.

·       Communicate findings across disciplines and contribute to publications and presentations.

Required Qualifications at this Level

·       Strong background in machine learning, deep learning, applied mathematics, or nonlinear dynamical systems.

·       Experience in modeling biological systems, computational biology, or related fields is a plus.

·       Excellent communication skills and ability to collaborate across diverse scientific backgrounds.

·       M.S., M.E. or Ph.D. in computational biology, engineering, physics, applied mathematics, computer science, or a related field.

We offer an intellectually stimulating and highly collaborative research environment at the interface of computation, biology, and engineering. This position provides opportunities to engage with diverse collaborators and contribute to cutting-edge research with real-world applications.Interested candidates should send their CV to Dr. Ophelia Venturelli (ophelia.venturelli@duke.edu).