Post Doctoral Research Associate

About the Role

The Castoe Lab at the University of Texas at Arlington is seeking a highly motivated and skilled postdoctoral researcher. Our laboratory studies genome biology and evolutionary genomics using integrative approaches with vertebrates and invertebrate parasites as model systems. Our research addresses fundamental questions in genome biology and evolution, including how novel gene regulatory networks evolve and function, how vertebrates control regenerative growth, how multiple synergistic processes shape genome structure and function, and how synergistic evolutionary processes result in speciation. These basic questions typically leverage snakes as model systems due to their unique phenotypic and genomic characteristics. Our work on schistosome parasites addresses more applied questions about how control efforts may drive distinct patterns of transmission and natural selection. Collaborative projects include COVID evolution, optimization of antibiotic compounds, the roles of stress response pathways, and epigenomics of trans-generational plasticity. This research addresses questions with relevance to human biology and health, as well as broader biological understanding of genome evolution, function, and the evolution of extreme traits. Research involves the generation and integrated computational analysis of diverse ‘omic’-scale datasets (including large population genomic, functional genomics, and single-cell omic datasets), and often leads to the development of new theory and computational approaches.

Key Responsibilities

• Conduct research in evolutionary genomics and speciation.
• Develop and test hypotheses about how selection, gene flow, recombination, and genomic architecture shape species boundaries and reproductive isolation.
• Analyze and compare genomic data from natural hybrid zones, integrating large genomic datasets from multiple populations, hybrid zones, and taxa to identify shared and lineage-specific patterns of divergence, introgression, and genomic coupling.
• Develop and implement computational methods, including building, benchmarking, and maintaining analytical tools and reproducible workflows for population genomics, using statistical modeling, population genetic simulations, and machine-learning approaches.
• Manage genomic data and research records, maintaining organized sequence data, metadata, analytical documentation, and sample records.
• Participate in field research and sample collection, including fieldwork in remote locations, collection and documentation of biological samples, and safe handling of venomous snakes.
• Publish and communicate research findings, leading and contributing to peer-reviewed manuscripts, presenting findings at scientific meetings, and preparing software, documentation, and data for public release.
• Collaborate across institutions, coordinating analyses, exchanging data and methods, and contributing to shared research objectives and publications.
• Assist students and other lab members with computational analyses and research methods, and contribute to project development, progress reporting, and proposal preparation.

Requirements & Tech Stack

• PhD in evolutionary biology, genetics, genomics, bioinformatics, or a closely related field by the position’s start date.
• Strong background in population and evolutionary genomics, including speciation, gene flow, and reproductive isolation.
• Demonstrated programming proficiency in one or more relevant languages, including R, Python, and C++.
• Experience analyzing large genomic datasets and developing or implementing reproducible computational workflows.
• Record of peer-reviewed publications relevant to the position.
• Demonstrated ability to communicate research findings and work both independently and collaboratively.

Preferred Qualifications

• Experience analyzing genomic data from hybrid zones, including comparative analyses across populations, hybrid zones, or taxa.
• Experience developing, benchmarking, and documenting population-genomic software or analytical tools.
• Experience with population genetic simulation frameworks, such as SLiM or msprime.
• Familiarity with machine-learning approaches relevant to genomic analysis.
• Experience using high-performance computing environments.
• Experience conducting fieldwork in remote locations and safely handling venomous snakes.
• Experience mentoring students or coordinating collaborative research activities.

Special Conditions for Eligibility

• Applicants must be legally able to accept work in the United States.
• Visa sponsorship is considered on an exception-only basis and is not routinely available.
• This position may require the ability to maintain the security or integrity of critical infrastructure, as defined by Texas Business and Commerce Code, and may authorize routine background checks.