Post Doctoral Research Associate

The University of Texas at Arlington Portal • Arlington, TX

1d

About The Position

The Castoe Lab at the University of Texas at Arlington seeks a highly motivated and skilled postdoctoral researcher to conduct research in evolutionary genomics and speciation. The lab studies genome biology and evolution using integrative approaches and vertebrate and invertebrate parasites as model systems. Research questions include how gene regulatory networks evolve and function, how vertebrates control regenerative growth, how processes shape genome structure and function, and how evolutionary processes contribute to speciation. The lab also studies schistosome parasites, COVID evolution, antibiotic compound optimization, stress response pathways, and epigenomics of trans-generational plasticity.

Research involves generating and computationally analyzing diverse omics datasets, including large population-genomic, functional-genomics, and single-cell datasets. The researcher will investigate genomic divergence, introgression, and reproductive isolation in natural hybrid zones; develop and implement computational methods; manage data and research records; participate in fieldwork and sample collection; publish and communicate findings; collaborate across institutions; and contribute to mentoring and project planning. Fieldwork may involve remote locations and safe handling of venomous snakes following training and applicable protocols.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• Conduct research in evolutionary genomics and speciation, developing and testing 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 datasets across populations, hybrid zones, and taxa to identify shared and lineage-specific patterns of divergence, introgression, and genomic coupling.
• Develop, implement, benchmark, and maintain computational tools and reproducible workflows for population genomics, using appropriate statistical modeling, population genetic simulations, and machine-learning approaches.
• Maintain organized sequence data, metadata, analytical documentation, and sample records to support reproducibility and collaboration.
• Support fieldwork in remote locations, including collection and documentation of biological samples and safe handling of venomous snakes after appropriate training and in accordance with applicable animal-use and safety protocols.
• Lead and contribute to peer-reviewed manuscripts, present findings at scientific meetings, and prepare software, documentation, and data for public release.
• Coordinate analyses, exchange data and methods, and contribute to shared research objectives and publications with collaborating investigators.
• Assist students and other lab members with computational analyses and research methods, and contribute to project development, progress reporting, and proposal preparation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree